Electronic device for automated user identification

ABSTRACT

This disclosure describes techniques for providing instructions when receiving biometric data associated with a user. For instance, an electronic device may detect a portion of a user, such as a hand. The electronic device may then determine locations of the portion of the user relative to the electronic device. Based on the locations, the electronic device may cause a visual indicator to provide instructions to the user for placing the portion of the user at a target location relative to the electronic device. For example, the visual indicator may emit light indicating that the portion of the user is off-centered, angled, too low, and/or too high. After providing the instructions and determining that the portion of the user is at the target location, the electronic device may capture at least an image of the portion of the user and use the image to identify an account.

BACKGROUND

Retailers, wholesalers, and other product distributors often managephysical stores that utilize cashiers or dedicated self-checkout standsto finalize transactions with customers. During these traditionalcheckout processes, customers may have to carry and use physical objectsfor payment or identification, such a credit card or debit card, adriver's license, a phone, and so forth. In the future, physical storesmay utilize various types of sensors to allow users to acquire and payfor items without cashiers or dedicated self-checkout stands. In someexamples, it may be desirable to identify customers using methods thatdo not require the use of physical objects and charge the appropriatecustomer accounts for items taken from the physical stores by thecustomers.

BRIEF DESCRIPTION OF FIGURES

The detailed description is set forth with reference to the accompanyingfigures. In the figures, the left-most digit(s) of a reference numberidentifies the figure in which the reference number first appears. Theuse of the same reference numbers in different figures indicates similaror identical items or features.

FIGS. 1A-1B collectively illustrate an example process for providinginstructions when capturing biometric data.

FIGS. 2A-2E illustrate various examples of electronic devices that maybe used to identify users using biometric-recognition techniques.

FIGS. 3A-3D illustrate various examples of an electronic deviceproviding instructions to horizontally center a hand.

FIGS. 4A-4D illustrate various examples of an electronic deviceproviding instructions to angle a hand.

FIGS. 5A-5D illustrate examples of target locations for placing a handof a user so that an electronic device can capture biometric data.

FIG. 6 illustrates an example of analyzing a hand in order to identifythe center of a palm of the hand.

FIG. 7 illustrates an example environment that includes an electronicdevice that determines that a user would like to enroll with auser-recognition system.

FIG. 8 illustrates an example environment including a block diagram ofone or more servers configured to support at least a portion of thefunctionality of a user-recognition system, as well as an example flowof data within the system for enrolling a user with the user-recognitionsystem.

FIG. 9 illustrates an example environment including a block diagram ofone or more servers configured to support at least a portion of thefunctionality of a user-recognition system, as well as an example flowof data within the system for identifying a user of the user-recognitionsystem and, potentially, updating the enrollment of the user.

FIG. 10 illustrates example components of an electronic deviceconfigured to support at least a portion of the functionality of auser-recognition system.

FIGS. 11A-11B collectively illustrate a flow diagram of an exampleprocess for providing instructions associated with placing a hand at atarget location relative to an electronic device.

FIG. 12 illustrates a flow diagram of an example process for providinginstructions associated with placing a portion of a user at a targetlocation relative to an electronic device.

FIG. 13 is a block diagram of an example materials handling facilitythat includes sensors and an inventory management system configured togenerate output regarding events occurring in the facility using thesensor data.

FIG. 14 illustrates a block diagram of one or more servers configured tosupport operation of the facility.

DETAILED DESCRIPTION

This disclosure is directed to an electronic device for identifyingusers using biometric-recognition techniques. For instance, theelectronic device may include a visual indicator that directs a user toplace a hand at a target location relative to the electronic device. Todirect the user, the electronic device may include one or more sensors,such as one or more distance sensors and/or imaging devices, thatdetermine the location of the hand relative to the electronic device.The electronic device may then cause the visual indicator to provideinstructions to the user for moving the hand to the target location.Once at the target location, the electronic device may use an imagingdevice to generate image data representing the hand (e.g., representingthe palm of the hand). The electronic device may then analyze featuredata generated using the image data, with respect to data stored inassociation with an account of the user, to identify the user.

For more details, the electronic device may include the visual indicatorthat instructs the user to place his or her hand at the target locationrelative to the electronic device. As described herein, the targetlocation relative to the electronic device may include both a targetvertical distance (e.g., z-direction) relative to the electronic deviceand a target horizontal location (e.g., x-direction and y-direction)relative to the electronic device. In some examples, the target verticaldistance may be associated with a distance above the electronic device,such as eight-five millimeters above the electronic device. However, inother examples, the target vertical distance may be associated with anyother distance above the electronic device. Additionally, in someexamples, the target horizontal location may be associated with themiddle of the electronic device, both in the x-direction and they-direction.

In some instances, the target vertical distance and/or the targethorizontal location may also allow for some offset when capturing thebiometric data. For example, the target vertical distance may allow forthe hand to be located within a range above the electronic device (e.g.,between seventy-five millimeters and ninety-five millimeters above theelectronic device). Additionally, the target horizontal location mayallow for the hand to be offset by a distance (e.g., twenty millimeters)in the x-direction and/or offset by a distance (e.g., twentymillimeters) the y-direction. In some instances, the distance in thex-direction is the same as the distance in the y-direction. In otherinstances, the distance in the x-direction is different than thedistance in the y-direction.

In some instances, the visual indicator may include light emittersarranged in pattern on a surface of the electronic device. The patternmay include, but is not limited to, a circle, a triangle, a square, apentagon, a hexagon, and/or any other pattern. For example, the visualindicator may include a light ring located on the surface of theelectronic device. Additionally, or alternatively, in some instances,the visual indicator may include a display that is shaped like thepattern on the surface of the electronic device. In either instance, theelectronic device uses the visual indicator to provide instructions tothe user for placing the hand of the user at the target locationrelative to the electronic device.

For example, the electronic device may initially cause the visualindicator to provide a first visual indication that the electronicdevice is not detecting a hand of the user. In some instances, the firstvisual indication may include the visual indicator being turned off. Forexample, if the visual indicator includes light emitters arranged in apattern on the surface of the electronic device, the first visualindication may include causing the light emitters to refrain fromemitting light. Additionally, or alternatively, in some instances, thefirst visual indication may include the visual indicator outputting aspecific color, pattern, and/or brightness of light. For example, andagain if the visual indicator includes light emitters arranged in apattern on the surface of the electronic device, the first visualindication may include causing the light emitters to emit a specificcolor of light, such as white.

While displaying the first visual indication, the electronic device maydetect the user's hand using the distance sensor(s) and/or the imagingdevice(s) (e.g., cameras). The electronic device may then use thedistance sensor(s) and/or the imaging device(s) to determine locationsof the hand relative to the electronic device. In some instances, theelectronic device may determine the locations of the user's hand at settime intervals. For instance, the electronic device may determine thelocations of the user's hand every millisecond, second, and/or the like.In some instances, such as when the electronic device is using theimaging device(s) to determine the locations, the electronic device maydetermine the locations of the hand using each frame represented by theimage data, every other frame represented by the image data, every fifthframe represented by the image data, and/or the like.

In some instances, the electronic device may initially determine thevertical distance of the hand relative to the electronic device. Forexample, the electronic device may use the distance sensor(s) todetermine the vertical distance. The electronic device may then analyzethe vertical distance of the hand with respect to the target verticaldistance. For example, the electronic device may determine if thevertical distance of the hand is within the vertical range associatedwith the target vertical distance. If the electronic device determinesthat the vertical distance of the hand is outside of the target verticaldistance (e.g., lower or higher than the vertical range) for theelectronic device, the electronic device may use the visual indicator toprovide instructions to the user.

For a first example, if the electronic device determines that thevertical distance to the user's hand is greater than the target verticaldistance, then the electronic device may cause the visual indicator topresent a second visual indication that the hand is too high. In someinstances, the second visual indication may include the visual indicatorflashing a light pattern. For example, and again if the visual indicatorincludes light emitters arranged in a pattern on the surface of theelectronic device, the second visual indication may include causing thelight emitters pulsate light at a given frequency. Additionally, oralternatively, in some instances, the second visual indication mayinclude the visual indicator outputting a specific color and/orbrightness of light. For example, and again if the visual indicatorincludes light emitters arranged in a pattern on the surface of theelectronic device, the second visual indication may include causing thelight emitters to emit a specific color of light, such as red.

For a second example, if the electronic device determines that thevertical distance to the user's hand is less than the target verticaldistance, then the electronic device may cause the visual indicator topresent a third visual indication that the hand is too low. In someinstances, the third visual indication may include the visual indicatoroutputting a specific color of light. For example, and again if thevisual indicator includes light emitters arranged in a pattern on thesurface of the electronic device, the third visual indication mayinclude causing the light emitters to emit a specific color of light,such as red. Additionally, or alternatively, in some instances, thethird visual indication may include the visual indicator flashing apattern and/or changing a brightness of light. For example, and again ifthe visual indicator includes light emitters arranged in a pattern onthe surface of the electronic device, the third visual indication mayinclude causing the light emitters pulsate at a given frequency.Additionally, or alternatively, in some instances,

The electronic device may continue to perform these processes until theelectronic device determines that the vertical distance of the hand isat the target vertical distance (e.g., within the vertical range). Insome instances, based on the determination, the electronic device maycause the visual indicator to present a fourth visual indication thatthe hand is located at the target vertical location. In some instances,the fourth visual indication may include the visual indicator outputtinga specific color of light. For example, and again if the visualindicator includes light emitters arranged in a pattern on the surfaceof the electronic device, the fourth visual indication may includecausing the light emitters to emit a specific color of light, such asblue. Additionally, or alternatively, in some instances, the fourthvisual indication may include the visual indicator flashing a lightpattern and/or changing a brightness of light. For example, and again ifthe visual indicator includes light emitters arranged in a pattern onthe surface of the electronic device, the fourth visual indication mayinclude causing the light emitters pulsate light at a given frequency.

The electronic device may then provide the user with instructions forcentering the hand (e.g., the palm of the hand) over the electronicdevice. For example, the electronic device may determine the horizontallocation of the hand with respect to the electronic device. In someinstances, the electronic device determines the horizontal locationusing the distance sensor(s). For instance, each distance sensor may beassociated with a respective horizontal location (e.g., horizontalposition) over the electronic device. For example, if the electronicdevice includes eight distance sensors, then a first distance sensor maybe associated with a front location, a second distance sensor may beassociated with a front-right location, a third distance sensor may beassociated with a right location, a fourth distance sensor may beassociated with a back-right location, a fifth distance sensor may beassociated with a back location, a sixth distance sensor may beassociated with a back-left location, a seventh distance sensor may beassociated with a left location, and an eighth distance sensor may beassociated with an front-left location. In this example, front/back maybe associated with the y-direction and left/right may be associated withthe x-direction.

The electronic device may then use the distance sensors to determine thehorizontal location of the hand with respect to the electronic device.For a first example, the electronic device may determine that thehorizontal location of the hand is to the left of the target horizontallocation when only the seventh distance sensor (and/or only the sixth,seventh, and eighth distance sensors) detect the hand. For a secondexample, the electronic device may determine that the horizontallocation of the hand is forward of the target horizontal location whenonly the first distance sensor (and/or only the first, second, andeighth distance sensors) detect the hand. Still, for a third example,the electronic device may determine that the horizontal location of thehand is at the target horizontal location when all of the distancesensors detect the hand.

Additionally, or alternatively, in some instances, the electronic devicemay determine the horizontal location of the user's hand using theimaging device(s). For example, and as described in more detail below,the electronic device may use one or more trained models to generatefeature data using the image data depicting the user's hand. The featuredata may indicate at least attributes associated with the hand, such as,but not limited to, various location(s) on the palm, a location of thecenter of the palm, location(s) on the fingers (e.g., the start of thefingers, the knuckle locations on the fingers, intersections between thefingers, etc.), location(s) on the thumb, a direction of the hand, apose of the hand, an orientation of the hand, and/or any otherattributes associated with the hand. Using the feature data, theelectronic device may determine the horizontal location of the user'shand relative to the electronic device. For example, the electronicdevice may use the center of the palm to determine the horizontallocation of the user's hand with respect to the imaging component.

The electronic device may provide instructions to the user to help theuser place the hand at the target horizontal location. For instance, ifthe horizontal location of the hand is to a side (e.g., the left) of thetarget horizontal location, then the electronic device may cause thevisual indicator to present a fifth visual indication that the hand isto the side of the target horizontal location. For a first example, andagain if the visual indicator includes light emitters arranged in apattern on the surface of the electronic device, the fifth visualindication may include causing the light emitters located on the side toemit light while causing the light emitters not located on the side torefrain from emitting light. For a second example, and again if thevisual indicator includes light emitters arranged in a pattern on thesurface of the electronic device, the fifth visual indication mayinclude causing the light emitters located on the side to emit a firstcolor of light (e.g., blue) while causing the light emitters not locatedon the side to emit a second, different color of light (e.g., red).

In some instances, while the electronic device is providing instructionsto the user for placing the hand at the target horizontal location, theelectronic device may also provide instructions that help the user keepthe hand approximately flat (e.g., horizontal) with respect to theelectronic device. For instance, if a portion of the hand, such as thefingers, falls outside of the target vertical distance, then theelectronic device may cause the visual indicator to present a sixthvisual indication that the portion of the hand is too low or too high.For a first example, and again if the visual indicator includes lightemitters arranged in a pattern on the surface of the electronic device,the sixth visual indication may include causing the light emitterslocated on the side at which the portion of the hand is located torefrain from emitting light while causing the light emitters not locatedon the side to emit light. For a second example, and again if the visualindicator includes light emitters arranged in a pattern on the surfaceof the electronic device, the sixth visual indication may includecausing the light emitters located on the side at which the portion ofthe hand is located to emit a first color of light (e.g., red) whilecausing the light emitters not located on the side to emit a second,different color of light (e.g., blue).

The electronic device may continue to provide the instructions to theuser until the electronic device detects that the hand of the user isproximate to the target location (e.g., the target vertical distance andthe target horizontal location). After the electronic device detectsthat the user's hand is located proximate to the target location, theelectronic device may cause the visual indicator to present a seventhvisual indication that the hand is located at the target location. Forexample, and again if the visual indicator includes light emittersarranged in a pattern on the surface of the electronic device, theseventh visual indication may include causing the light emitters to emita color of light, a light pattern, or a brightness of light.Additionally, in instances where the user has already enrolled with auser-recognition system, the user-recognition system may perform theprocesses described herein to identify the user profile associated withthe user. In instances where the user has yet to enroll with theuser-recognition system, the electronic device may provide one or moreadditional instructions for receiving additional information forenrolling with the user-recognition system.

For example, and as described below, users may enroll with theuser-recognition system that utilizes various biometric-basedrecognition techniques so users may be identified without having tocarry or use traditional forms of identification, such as showing an IDcard or accessing their personal phone. The user-recognition system mayrecognize, or identify, enrolled users for various purposes, such as forautomating traditional checkout experiences in a materials handlingfacility (or “facility”) by charging appropriate user accounts withpurchases of items selected by enrolled users in the facility.

In one illustrative example, the systems and techniques are used torecognize or identify users within a materials handling facility, whichmay include, or have access to, an inventory-management system. Theinventory-management system may be configured to maintain informationabout items, users, conditions of the facility, and so forth. Forexample, the inventory-management system may maintain data indicative ofa result of different events that occur within the facility, such aswhat items a particular user picks or returns, a location of theparticular user, and so forth.

Operation of the inventory-management system may be supported by sensordata acquired by one or more sensors. The sensor data may include imagedata acquired by imaging devices such as cameras, information acquiredfrom radio frequency tags, weight sensors, and so forth. For example,the inventory-management system may automatically identify an itemremoved from an inventory location as well as a user that removed theitem. In response, the inventory-management system may automaticallyupdate a virtual shopping cart of the user.

Traditionally, when a user has finished their shopping session, the userwould have to pay for their items by having a cashier scan their items,or by using dedicated self-checkout stands. The techniques describedherein reduce friction in the traditional checkout experience byrecognizing or identifying a user enrolled for use of theuser-recognition system and charging a user account for that user withthe cost of the items included in their virtual shopping cart. Accordingto the techniques described herein, a user enrolled with theuser-recognition system may need only provide biometric information by,for example, scanning a palm of the user at an imaging device, scanninga fingerprint of the user, looking at a camera of an electronic devicelocated in the facility, or the like in order to be identified by theuser-recognition system.

To utilize the user-recognition system, a user may request to beenrolled by interacting with the electronic device positioned in afacility. For example, the user may select an enroll option on a displayof the electronic device, issue a voice or GUI-based command requestingto be enrolled, insert a user ID card into the electronic device, and/orsimply present their hand or palm before the electronic device to promptthe enrollment process.

Upon requesting to be enrolled in the user-recognition system, theelectronic device may, with permission and/or upon explicit request bythe user, begin collecting various types of biometric data, and/or otherdata, for the user. For example, the electronic device may include theimaging device(s) that begin capturing image data (e.g., an individualimage, a sequence of images, a video, etc.) of at least a portion of theuser, such as a palm of the user, a face of the user, or the like. Inthe example of the palm, and as discussed above, the electronic devicemay request that the user move their hand to different angles and/ororientations as the electronic device captures the image data and mayalso capture image data under different lighting conditions (e.g., noflash, flash, different light polarizations, etc.), to generate imagedata representing the palm of the user under different environmentalconditions.

In some examples, the user may already have an account registered withthe inventory-management system to pay for items selected during ashopping session. In such examples, the electronic device may determinea user account with which the user is registered in various ways, suchas by requesting that the user insert a personal ID card (e.g., driver'slicense), scan a barcode that may be presented on a display of a phoneof the user, login with his or her login credentials, and so forth.

Once the electronic device has obtained the image data representing thepalm or other potion of the user, the electronic device may utilize thisdata to enroll the user with the user-recognition system. In someexamples, the user-recognition system may be implemented entirely on theelectronic device, which may include the software, firmware, and/orhardware components to implement the techniques described herein.However, in some examples, the user-recognition system may beimplemented according to a split architecture where the electronicdevice performs client-side enrollment and identification techniques,and more intensive and/or advanced processing may be performed using abackend, server-based implementation. For example, the user-recognitionsystem may include one or more network-based computing devicespositioned at a separate location in the facility, and/or at a remote,cloud-based location. The network-based devices may include variouscomponents for implementing the user-recognition system.

In such examples, the electronic device may send the image data, and/orfeature data generated by the user recognition device using the imagedata, to the network-based devices to enroll the user for theuser-recognition system. The network-based devices of theuser-recognition system may perform various processing techniques on theimage data and/or feature data such that the user-recognition system isable to identify the user from subsequently received image data and/orfeature data.

The user-recognition system may analyze the image data to determinevarious features of the user. For example, the user-recognition systemmay extract and/or generate, based on the image data, palm-feature datarepresenting the palm of the user. This palm-feature data may representinformation that is potentially unique to the palm of the user, such asthe pattern of creases in the user's palm, the pattern of veins of theuser's palm, the geometry of one or more portions of the user's hand(e.g., finger sizes/shape, palm size/shape, etc.), and/or the like. Theuser-recognition system may utilize any type of processing techniques togenerate the palm-feature data and may represent the palm of the userdepicted in the image data using various types of data structures, suchas feature vectors. In some examples, the user-recognition system mayinclude one or more trained models (e.g., machine-learning models) thathave been trained to receive image data of a user as input, and outputfeature vectors representing a palm of the user. Generally, the trainedmodel(s) may comprise any type of models, such as machine-learningmodels (e.g., artificial neural networks, convolution neural networks(CNNs), classifiers, random-forest models, etc.) that may be trained toidentify a palm of a user and/or one or more other portions of the user(e.g., face, etc.).

Upon obtaining the feature data that represents the palm of the user,the user-recognition system may store the feature data in an enrollmentdatabase and associate the feature data with a user profile for thatspecific user. In this way, when subsequent image data is received for auser at an electronic device, the feature data stored in the enrollmentdatabase may be compared with the feature data generated from thesubsequent image data to identify a user profile for the userrepresented in the subsequent image data and audio data.

In this way, the user may be enrolled for use of the user-recognitionsystem such that, after completing subsequent shopping sessions, theuser may checkout by placing his or her palm over an imaging componentof an electronic device to allow the user-recognition system toautomatically recognize the user. The electronic device may detect thepresence of the user (e.g., detect the palm, detect a face, detect thespeech utterance, detect a touch input via a touch display, etc.), andbegin streaming image data and audio data to the backend devices of theuser-recognition system. The backend devices of the user-recognitionsystem may then utilize the trained model(s) to extract feature data andcompare that feature data to stored feature data for user profiles ofenrolled users. In addition, or in the alternative, the user may scanhis or her palm for recognition upon entering the facility and, in someinstances, may simply exit the facility with his or her picked items andwithout again scanning his or her palm. In these instances, the user maybe identified upon entry and located by the system as the user movesabout the facility, such that the user may “just walk out” withoutfurther interaction with associates or devices at the facility.

Although the techniques described herein are primarily with reference toidentifying users for the purpose of identifying a user account tocharge for items selected from a materials handling facility, thetechniques are equally applicable to any industry in which userrecognition may be helpful. For instance, the user-recognition systemmay be implemented for security purposes such as accessing lockedlocations, accessing user accounts via computing devices, accessing bankaccounts, and so forth. Further, while certain types of machine-learningmodels and algorithms are discussed herein, the techniques may beemployed using other types of technologies and are generally scalable todifferent computer-based implementations.

Additionally, although the techniques described above include theelectronic device determining the locations of the hand, in otherexamples, the backend devices may determine the locations of the hand.For example, the electronic device may send the sensor data generatedusing the one or more sensors to the backend devices. The backenddevices may then perform the processes described herein, with respect tothe electronic device, to determine the locations of the hand.Additionally, the backend devices may send, to the electronic device,data indicating the locations of the hand. The electronic device maythen use the data to update the user interfaces when providing theinstructions to the user.

The following description describes use of the techniques within amaterials handling facility. The facility described herein may include,but is not limited to, warehouses, distribution centers, cross-dockingfacilities, order fulfillment facilities, packaging facilities, shippingfacilities, rental facilities, libraries, retail stores, wholesalestores, museums, or other facilities or combinations of facilities forperforming one or more functions of materials (inventory) handling. Inother implementations, the techniques described herein may beimplemented in other facilities or situations.

Certain implementations and embodiments of the disclosure will now bedescribed more fully below with reference to the accompanying figures,in which various aspects are shown. However, the various aspects may beimplemented in many different forms and should not be construed aslimited to the implementations set forth herein. The disclosureencompasses variations of the embodiments, as described herein. Likenumbers refer to like elements throughout.

FIGS. 1A-1B collectively illustrate an example process 100 for providinginstructions when capturing biometric data. At 102, an electronic device104 may detect a hand of a user. For instance, a visual indicator 108 ofthe electronic device 104 may be displaying a first visual indicationthat instructs the user to place the hand 106 over the electronic device104. In the example of FIGS. 1A-1B, the visual indicator 108 includes alight ring located around a top surface of the electronic device 104.However, in other examples, the visual indicator 108 may include anyother shape on one or more surfaces of the electronic device 104. Asshown in the example of FIGS. 1A-1B, the first visual indication mayinclude refraining from emitting light. However, in other examples, thefirst visual indication may include emitting a color, brightness, and/orpattern of light.

The electronic device 104 may then use one or more sensors, which arediscussed in more detail with regard to FIGS. 2A-2D, to detect the hand106. For example, the electronic device 104 may use one or more distancesensors to detect the hand 106 located over the electronic device 104.For another example, the electronic device 104 may use one or moreimaging devices to generate image data representing the hand 106. Theelectronic device 104 may then analyze the image data to determine thatthe hand 106 is located over the electronic device 104.

In some instances, and as illustrated in the example of FIGS. 1A-1B, theelectronic device 04 may output sound 110 that indicates that theelectronic device 104 detected the hand 106. For a first example, thesound 110 may include one or more words indicating that the electronicdevice 104 detected the hand 106 (e.g., “Hand Detected”). For a secondexample, the sound 110 may include one or more noises (e.g., pings,humming, constant tone, etc.) that lets the user know that the hand 106was detected.

At 112, the electronic device 104 may display a first visual indicationthat the hand 106 is too high. For instance, the electronic device 104may determine that the hand 106 of the user is higher than a targetvertical distance for the electronic device 104. In some instances, theelectronic device 104 determines the vertical distance of the hand 106using the one or more distance sensors. Additionally, or alternatively,in some instances, the electronic device 104 determines the verticaldistance of the hand 106 by analyzing image data generated by the one ormore imaging devices. In either of the instances, the electronic device104 then compares the vertical distance of the hand 106 to the targetvertical distance, which may include a vertical range, to determine thatthe vertical distance of the hand 106 is greater than the targetvertical distance.

The electronic device 104 may then display the first visual indicationthat the hand 106 is too high. In some instances, and as illustrated inthe example of FIGS. 1A-1B, the first visual indication may include thevisual indicator 108 flashing a pattern of light (which is illustratedby the crosses within the circles). For example, the first visualindication may include causing the light emitters of the visualindicator 108 to pulsate the light at a given frequency. Additionally,or alternatively, in some instances, the first visual indication mayinclude the visual indicator 108 outputting a specific color and/orbrightness of light. For example, the first visual indication mayinclude causing the light emitters of the visual indicator 108 to emit aspecific color of light, such as red.

In some instances, and as illustrated in the example of FIGS. 1A-1B, theelectronic device 104 may output sound 114 that indicates that the hand106 is too high. For a first example, the sound 114 may include one ormore words indicating that the hand is too high (e.g., “Please LowerYour Hand”). For a second example, the sound 110 may include one or morenoises (e.g., pings, humming, constant tone, etc.) that lets the userknow that the hand 106 is too high.

At 116, the electronic device 104 may display a second visual indicationthat the hand is off-centered. For instance, the electronic device 104may determine that the hand 106 of the user is located outside of thetarget horizontal location for the electronic device 104. In someinstances, the electronic device 104 determines the horizontal locationof the hand 106 using the one or more distance sensors. Additionally, oralternatively, in some instances, the electronic device 104 determinesthe horizontal location of the hand 106 by analyzing image datagenerated by the one or more imaging devices. In either of theinstances, the electronic device 104 then compares the horizontallocation of the hand 106 to the target horizontal location, which mayallow for some offset in the x-direction and/or the y-direction, todetermine that the horizontal location of the hand 106 is locatedoutside of the target horizontal location.

The electronic device 104 may then display the second visual indicationthat the hand 106 is off-centered. For instance, since the horizontallocation of the hand 106 is too far to a side 118 of the electronicdevice 104, then the electronic device may cause the visual indicator108 to display the second visual indication that the hand 106 is locatedtoo far to the side 118. For a first example, and as illustrated in theexample of FIGS. 1A-1B, the second visual indication may include causingthe light emitters of the visual indicator 108 that are located on theside 118 to emit light (which is illustrated by the solid black circles)while causing the light emitters of the visual indicator 108 that arenot located on the side 118 to refrain from emitting light (which isillustrated by the solid white circles). For a second example, thesecond visual indication may include causing the light emitters of thevisual indicator 108 that are located on the side 118 to emit a firstcolor of light (e.g., blue) while causing the light emitters of thevisual indicator 108 that are not located on the side 118 to emit asecond, different color of light (e.g., red).

In some instances, and as illustrated in the example of FIGS. 1A-1B, theelectronic device 104 may output sound 120 that indicates that the hand106 is off-centered. For a first example, the sound 112 may include oneor more words indicating that the hand 106 is of-centered (e.g., “YourHand Is Off-Centered” or “Please Move Your Hand Back”). For a secondexample, the sound 120 may include one or more noises (e.g., pings,humming, constant tone, etc.) that lets the user know that the hand 106is off-centered.

At 122, the electronic device 104 may display a third visual indicationthat the hand 106 is angled. For instance, the electronic device 104 maydetermine that the hand 106 of the user is angled with respect to theelectronic device 104. In some instances, the electronic device 104determines the angle of the hand 106 using the one or more distancesensors. For instance, the electronic device 104 may determine that thehand 106 is located closer to a first distance sensor than a seconddistance sensor. Additionally, or alternatively, in some instances, theelectronic device 104 determines the angle of the hand 106 by analyzingimage data generated by the one or more imaging devices. In either ofthe instances, the electronic device 104 then compares the angle of thehand 106 to a target angle. Based on the comparison, the electronicdevice 104 may determine that the angle of the hand 106 is greater thanthe target angle.

The electronic device 104 may then display the third visual indicationthat the hand 106 is angled. For instance, since the angle of the hand106 is such that the hand 106 is closer to the side 118 of theelectronic device 104 than the other side of the electronic device 104,then the electronic device 104 may cause the visual indicator 108 todisplay the third visual indication that the hand 106 is angled towardsthe side 118. For a first example, and as illustrated in the example ofFIGS. 1A-1B, the third visual indication may include causing the lightemitters of the visual indicator 108 that are located on the side 118 toemit a first color of light (which is illustrated by the solid greycircles) while causing the light emitters of the visual indicator 108that are not located on the side 118 to emit a second color of light(which is illustrated by the solid black circles). For a second example,the third visual indication may include causing the light emitters ofthe visual indicator 108 that are located on the side 118 to refrainfrom emitting light while causing the light emitters of the visualindicator 108 that are not located on the side 118 to emit a color oflight.

In some instances, and as illustrated in the example of FIGS. 1A-1B, theelectronic device 104 may output sound 124 that indicates that the hand106 is angled. For a first example, the sound 124 may include one ormore words indicating that the hand 106 is angled (e.g., “Your Hand IsAngled” or “Please Flatten Your Hand”). For a second example, the sound1124 may include one or more noises (e.g., pings, humming, constanttone, etc.) that lets the user know that the hand 106 is angled.

At 126, the electronic device 104 may display a fourth visual indicationthat the hand 106 is at a target location. For instance, the electronicdevice 104 may determine the location and/or the angle of the hand 106using the one or more distance sensors. Additionally, or alternatively,in some instances, the electronic device 104 determines the locationand/or the angle of the hand 106 by analyzing image data generated bythe one or more imaging devices. In either of the instances, theelectronic device 104 then compares the location of the hand 106 to thetarget location and, based on the comparison, determines that the hand106 of the user is at the target location. Additionally, the electronicdevice 104 compares the angle of the hand 106 to the target angle and,based on the comparison, determines that the angle of the hand 106satisfies the threshold angle.

The electronic device 104 may then display the fourth visual indicationthat the hand 106 is at the target location. For a first example, and asillustrated in the example of FIGS. 1A-1B, the fourth visual indicationmay include causing the light emitters of the visual indicator 108 toemit a color of light (which is illustrated by the solid black circles).For a second example, the fourth visual indication may include causingthe light emitters of the visual indicator 108 to emit a flashing lightpattern and/or emit light at a specific brightness.

In some instances, and as illustrated in the example of FIGS. 1A-1B, theelectronic device 104 may output sound 128 that indicates that the hand106 is at the target location. For a first example, the sound 128 mayinclude one or more words indicating that the hand 106 is at the targetlocation (e.g., “Your Hand Is At The Target Location”). For a secondexample, the sound 110 may include one or more noises (e.g., pings,humming, constant tone, etc.) that lets the user know that the hand 106is at the target location.

At 130, the electronic device 104 may identify an account usingbiometric data associated with the hand 106. For instance, theelectronic device 104 may generate, using the one or more imagingdevices, image data representing the hand 106. The electronic device 104may then analyze the image data to determine feature data correspondingto the hand 106. Additionally, the electronic device 104 may analyze thefeature data with respect to feature data stored in association with theaccount. Based on the analysis, the electronic device 104 may determinethat the feature data corresponding to the hand 106 matches the featuredata stored in association with the account. As such, the electronicdevice 104 may identify the account.

In some instances, and as illustrated in the example of FIGS. 1A-1B, theelectronic device 104 may output sound 132 that indicates that theaccount has been identified. For a first example, the sound 132 mayinclude one or more words indicating that the account has beenidentified (e.g., “We Have Identified An Account”). For a secondexample, the sound 132 may include one or more noises (e.g., pings,humming, constant tone, etc.) that lets the user know that the accounthas been identified.

FIGS. 2A-2D illustrate various examples of electronic devices 202(1)-(4)that may be used to identify users using biometric-recognitiontechniques. In some instances, one or more of the electronic devices202(1)-(4) may correspond to the electronic device 104 from the exampleof FIGS. 1A-1B.

As shown in the example of FIG. 2A, the electronic device 202(1) mayinclude a circular shape. However, in other examples, the electronicdevice 202(1) (as well as one or more of the electronic devices202(2)-(4)) may include a shape other than a circle. The electronicdevice 202(1) includes distance sensors 204(1)-(6) (also referred to as“distance sensors 204”) located in a circle around the surface of theelectronic device 202(1). Although the example of FIG. 2A illustratessix distance sensors 204, in other examples, the electronic device202(1) may include any number of distance sensors 204. Additionally,although the example of FIG. 2A illustrates the distance sensors 204arranged in a circle and spaces equal apart from one another, in otherexamples, the distance sensors 204 may include any other arrangement onthe surface of the electronic device 202(1).

The electronic device 202(1) also includes a visual indicator 206located around an outer edge of the surface of the electronic device202(1). The visual indicator 206 includes light emitters 208 (althoughonly one is illustrated for clarity reasons) spaced around the entiretyof the visual indicator 206. However, in other examples, the visualindicator 206 may include a shape other than a circle. Additionally, inother examples, the visual indicator 206 may include more or less lightemitters 208. Furthermore, in other examples, the visual indicator 206may include a display.

The electronic device 202(1) also includes an imaging device 210 locatedat the center of the electronic device 202(1). In some instances, theimaging device 210 may include a camera (e.g., a Red-Green-Blue (RGB)camera, an infrared camera, a near-infrared camera, etc.). Although theexample of FIG. 2A illustrates the imaging device 210 located at thecenter of the electronic device 202(1), in other examples, the imagingdevice 210 may be located at a different location of the electronicdevice 202(1). Additionally, in other examples, the imaging device 210may include more than one imaging device. For example, the electronicdevice 202(1) may include a first imaging device that generates firstimage data for performing the biometric-recognition techniques describedherein. The electronic device 202(1) may also include a second imagingdevice that generates second image data used for other processingpurposes, such as verify that the hand of the user is an actual hand(e.g., for protecting against biometric spoofing).

For example, such as when the hand is at the target location, theelectronic device 202(1) may cause the visual indicator 206 to emitlight. In some instances, the light may include a specific color oflight and/or specific pattern of light (e.g., flashing the light at agiven frequency). The light may be configured such that the imagingdevice 210 (and/or another imaging device) is able to generate imagedata that can be analyzed to determine whether the hand is an actualhand, in order to protect against biometric spoofing.

FIG. 2B illustrates another electronic device 202(2) that may be used toidentify users using biometric-recognition techniques. In the example ofFIG. 2B, the electronic device 202(2) may also include the visualindicator 206 and the imaging device 210. However, the electronic device202(2) now includes a single distance sensor 212 located proximate tothe center of the electronic device 202(2). While the example of FIG. 2Billustrates a single distance sensor 212 located proximate to the centerof the electronic device 202(2), in other examples, the electronicdevice 202(2) may include any number of distance sensors 212 locatedproximate to the center of the electronic device 202(2).

FIG. 2C illustrates another electronic device 202(3) that may be used toidentify users using biometric-recognition techniques. In the example ofFIG. 2C, the electronic device 202(3) may also include the visualindicator 206 and the imaging device 210. However, the electronic device202(3) does not include a distance sensor. Rather, the electronic device202(3) may use the imaging device 210 to determine the locations ofhands, using the processes described in more detail with regard to FIG.6.

FIG. 2D illustrates another electronic device 202(4) that may be used toidentify users using biometric-recognition techniques. In the example ofFIG. 2D, the electronic device 202(4) may include the distance sensors204 and the imaging device 210. However, in other examples, theelectronic device 202(4) may include the layout of the electronic device202(2) and/or the electronic device 202(3) for the distance sensor(s)and/or the imaging device 210. The electronic device 202(4) alsoincludes a visual indicator 214 located around an outer edge of thesurface of the electronic device 202(4). The visual indicator 214 mayinclude a display device. However, in other examples, the visualindicator 214 may include a shape other than a circle.

FIG. 2E illustrates another electronic device 202(5) that may be used toidentify users using biometric-recognition techniques. In the example ofFIG. 2E, the electronic device 202(5) may include at least a firstvisual indicator 218(1), a second visual indicator 218(2), and a thirdvisual indicator 218(3) (referred to collectively as “visual indicators218”). The electronic device 202(5) may use the various visualindicators 218 to provide instructions to the user. For example, thethird visual indicator 218(3) may be activated when the hand of the useris too close the electronic device 202(5), the second visual indicator218(2) may be activated when the hand is at the target verticaldistance, and the first visual indicator 218(1) may be used when thehand is too far from the electronic device 202(5). This way, the usercan determine when the hand is at the target vertical distance based onthe second visual indicator 218(2) being activated.

In some instances, each of the visual indicators 218 may also beconfigured to provide instructions for moving the hand to the targethorizontal location, using the processes described herein. Additionally,or alternatively, in some instances, only the second visual indicator218(2) may be configured to provide instructions for moving the hand tothe target horizontal location. In some instances, each of the visualindicators 218 may be similar to the visual indicator 206 and includelight emitters 208.

While the examples of FIGS. 2A-2E illustrate a few exampleconfigurations for electronic devices, in other examples, an electronicdevice may include additional and/or alternative configurations. Forexample, an electronic device may additionally or alternatively includeone or more visual indicators located on other surfaces of theelectronic device, such as the sides. This way, even if the hand isblocking a portion of the visual indicator located on the top surface,the electronic device is still able to provide instructions to the userusing the one or more other visual indicators.

FIGS. 3A-3D illustrate various examples of the electronic device 104providing instructions to horizontally center a hand. For instance, andas shown in the example of FIG. 3A, the electronic device 104 maydetermine the horizontal location of the hand of the user. In someinstances, the electronic device 104 determines the horizontal locationusing distance sensors 302 (although only one is labeled for clarityreasons). For example, and as illustrated, the left distance sensor 302of the electronic device 104 may detect the hand of the user, which isrepresented by the diagonal lines associated with the left distancesensor 302. However, the other distance sensors 302 of the electronicdevice 104 may not detect the hand of the user. As such, the electronicdevice 104 may determine that the hand of the user is not located at thetarget horizontal location and/or located too far to the left side ofthe electronic device 104.

As such, the electronic device 104 may cause the visual indicator 108 toprovide instructions to the user. In the example of FIG. 3A, the visualindicator 108 may provide the instructions by indicating to the userthat the hand is located too far to the left. As shown, the visualindicator 108 may provide such instructions by causing light emitters304 (although only one is illustrated for clarity reasons) located atthe left side of the visual indicator 108 to emit light, which isillustrated by the solid black circles, but cause all of the other lightemitters 304 to refrain from emitting light, which is illustrated by thesolid white circles. In some instances, each light emitter 304 isassociated with at least one of the distance sensors 302 such that therespective light emitters 304 emit light when the distance sensor 302detects the hand. For instance, and in the example of FIG. 3A, the lightemitters 304 that are emitting the light are associated with at leastthe left distance sensor 302.

As shown in the example of FIG. 3B, the electronic device 104 may againdetermine the horizontal location of the hand of the user. In someinstances, the electronic device 104 determines the horizontal locationusing the distance sensors 302. For example, and as illustrated, theback distance sensor 302, the back-left distance sensor 302, the leftdistance sensor 302, the front-left distance sensor 302, and the frontdistance sensor 302 of the electronic device 104 may detect the hand ofthe user, which is represented by the diagonal lines associated withsuch distance sensors 302. However, the other distance sensors 302 ofthe electronic device 104 may not detect the hand of the user. As such,the electronic device 104 may again determine that the hand of the useris not located at the target horizontal location and/or located too farto the left side of the electronic device 104. However, the electronicdevice 104 may also determine that the horizontal location of the handis now located closer to the target horizontal location than in theexample of FIG. 3A.

As such, the electronic device 104 may cause the visual indicator 108 toprovide instructions to the user. In the example of FIG. 3B, the visualindicator 108 may provide the instructions by indicating to the userthat the hand is located too far to the left. As shown, the visualindicator 108 may provide such instructions by causing the lightemitters 304 located at the back, back-left, left, front-left, and frontof the visual indicator to emit light, which is illustrated by the solidblack circles, but cause all of the other light emitters 304 to refrainfrom emitting light, which is illustrated by the solid white circles. Asdiscussed above, in some instances, each light emitter 304 is associatedwith at least one of the distance sensors 302 such that the respectivelight emitters 304 emit light when the distance sensor 302 detects thehand. For instance, and in the example of FIG. 3B, the light emitters304 that are emitting the light might be associated with the distancesensors 302 that detected the hand.

As shown in the example of FIG. 3C, the electronic device 104 may againdetermine the horizontal location of the hand of the user. In someinstances, the electronic device 104 determines the horizontal locationusing the distance sensors 302. For example, and as illustrated, theback distance sensor 302, the back-left distance sensor 302, the leftdistance sensor 302, the front-left distance sensor 302, the frontdistance sensor 302, the front-right distance sensor 302, and the rightdistance sensor 302 of the electronic device 104 may detect the hand ofthe user, which is represented by the diagonal lines associated withsuch distance sensors 302. However, the back-right distance sensor 302of the electronic device 104 may not detect the hand of the user. Assuch, the electronic device 104 may again determine that the hand of theuser is not located at the target horizontal location and/or located toofar to the front-left side of the electronic device 104. However, theelectronic device 104 may also determine that the horizontal location ofthe hand is now located closer to the target horizontal location in theexample of FIG. 3B.

As such, the electronic device 104 may cause the visual indicator 108 toprovide instructions to the user. In the example of FIG. 3C, the visualindicator 108 may provide the instructions by indicating to the userthat the hand is located too far to the front-left of the electronicdevice 104. As shown, the visual indicator 108 may provide suchinstructions by causing the light emitters 304 located at the back,back-left, left, front-left, front, front-right, and right of the visualindicator to emit light, which is illustrated by the solid blackcircles, but cause all of the other light emitters 304 to refrain fromemitting light, which is illustrated by the solid white circles. Asdiscussed above, in some instances, each light emitter 304 is associatedwith at least one of the distance sensors 302 such that the respectivelight emitters 304 emit light when the distance sensor 302 detects thehand. For instance, and in the example of FIG. 3C, the light emitters304 that are emitting the light might be associated with the distancesensors 302 that detected the hand.

Finally, and as shown in the example of FIG. 3D, the electronic device104 may again determine the horizontal location of the hand of the user.In some instances, the electronic device 104 determines the horizontallocation using the distance sensors 302. For example, and asillustrated, all of the distance sensors 302 of the electronic device104 may detect the hand of the user, which is represented by thediagonal lines associated with the distance sensors 302. As such, theelectronic device 104 may determine that the horizontal location of thehand is now located at the target horizontal location. As such, theelectronic device 104 may cause the visual indicator 108 to notify theuser that the hand is located at the correct horizontal location. In theexample of FIG. 3D, the visual indicator 108 may provide thenotification by causing all of the light emitters 304 to emit light,which is illustrated by the solid black circles.

It should be noted that, in some instances, the electronic device 104may then attempt to identify an account of the user using image datarepresenting the hand of the user. In some instances, if the electronicdevice cannot identify an account, such as if the user has yet toregister an account, the electronic device 104 may provide anotification that there is an error and/or an account should be created.In some instances, the electronic device 104 may provide thenotification by causing the visual indicator 108 emit a color of light,a light pattern, and/or a brightness of light, similar to one or more ofthe examples illustrated herein. Additionally, in some instances, if theelectronic device identifies an account, such as if the user has alreadyregistered the account, the electronic device 104 may provide anotification that the account was identified. In some instances, theelectronic device 104 may provide the notification by causing the visualindicator 108 emit a color of light, a light pattern, and/or abrightness of light, similar to one or more of the examples illustratedherein

FIGS. 4A-4D illustrate various examples of the electronic device 104providing instructions to angle a hand. For instance, and as shown inthe example of FIG. 4A, the electronic device 104 may determine theangle of the hand of the user. In some instances, the electronic device104 determines the angle using the distance sensors 302. For example,and as illustrated, the back-left distance sensor 302, the left distancesensor 302, and the front-left distance sensor 302 of the electronicdevice 104 may detect a first vertical distance of the hand of the user,which is represented by the diagonal lines, while the other distancesensors 302 detect a second vertical distance of the hand of the user.The electronic device 104 may then determine that the first verticaldistance is outside of the target vertical distance (e.g., the verticalrange) while the second vertical distance is within the target verticaldistance.

As such, the electronic device 104 may cause the visual indicator 108 toprovide instructions to the user. In the example of FIG. 4A, the visualindicator 108 may provide the instructions by indicating to the userthat the left portion of the hand is too close to the electronic device104. As shown, the visual indicator 108 may provide such instructions bycausing the light emitters 304 located at the back-left, the left, andthe top-left of the visual indicator 108 to emit a first color of light,which is illustrated by the solid grey circles, but cause all of theother light emitters 304 to emit a second color of light, which isillustrated by the solid black circles. However, in other examples, thevisual indicator 108 may provide the instructions by causing the lightemitters 304 located at the back-left, the left, and the top-left of thevisual indicator 108 to refrain from emitting light while causing all ofthe other light emitters 304 to emit light.

As shown in the example of FIG. 4B, the electronic device 104 may againdetermine the angle of the hand of the user. In some instances, theelectronic device 104 determines the angle using the distance sensors302. For example, and as illustrated, the top-left distance sensor 302,the top distance sensor 302, and the top-right distance sensor 302 ofthe electronic device 104 may detect a first vertical distance of thehand of the user, which is represented by the diagonal lines, while theother distance sensors 302 detect a second vertical distance of the handof the user. The electronic device 104 may then determine that the firstvertical distance is outside of the target vertical distance (e.g., thevertical range) while the second vertical distance is within the targetvertical distance.

As such, the electronic device 104 may cause the visual indicator 108 toprovide instructions to the user. In the example of FIG. 4B, the visualindicator 108 may provide the instructions by indicating to the userthat the top portion of the hand is too close to the electronic device104. As shown, the visual indicator 108 may provide such instructions bycausing the light emitters 304 located at the top-left, the top, and thetop-right of the visual indicator 108 to emit a first color of light,which is illustrated by the solid grey circles, but cause all of theother light emitters 304 to emit a second color of light, which isillustrated by the solid black circles. However, in other examples, thevisual indicator 108 may provide the instructions by causing the lightemitters 304 located at the top-left, the top, and the top-right of thevisual indicator 108 to refrain from emitting light while causing all ofthe other light emitters 304 to emit light.

As shown in the example of FIG. 4C, the electronic device 104 may againdetermine the angle of the hand of the user. In some instances, theelectronic device 104 determines the angle using the distance sensors302. For example, and as illustrated, the right distance sensor 302 ofthe electronic device 104 may detect a first vertical distance of thehand of the user, which is represented by the diagonal lines, while theother distance sensors 302 detect a second vertical distance of the handof the user. The electronic device 104 may then determine that the firstvertical distance is outside of the target vertical distance (e.g., thevertical range) while the second vertical distance is within the targetvertical distance.

As such, the electronic device 104 may cause the visual indicator 108 toprovide instructions to the user. In the example of FIG. 4C, the visualindicator 108 may provide the instructions by indicating to the userthat the right portion of the hand is too close to the electronic device104. As shown, the visual indicator 108 may provide such instructions bycausing the light emitters 304 located at the right of the visualindicator 108 to emit a first color of light, which is illustrated bythe solid grey circles, but cause all of the other light emitters 304 toemit a second color of light, which is illustrated by the solid blackcircles. However, in other examples, the visual indicator 108 mayprovide the instructions by causing the light emitters 304 located atthe right of the visual indicator 108 to refrain from emitting lightwhile causing all of the other light emitters 304 to emit light.

Finally, and as shown in the example of FIG. 4D, the electronic device104 may again determine the angle of the hand of the user. In someinstances, the electronic device 104 determines the angle using thedistance sensors 302. For example, and as illustrated, the rightdistance sensor 302, the back-right distance sensor 302, the backdistance sensor 302, the back-left distance sensor 302, and the leftdistance sensor 302 of the electronic device 104 may detect a firstvertical distance of the hand of the user, which is represented by thediagonal lines, while the other distance sensors 302 detect a secondvertical distance of the hand of the user. The electronic device 104 maythen determine that the first vertical distance is outside of the targetvertical distance (e.g., the vertical range) while the second verticaldistance is within the target vertical distance.

As such, the electronic device 104 may cause the visual indicator 108 toprovide instructions to the user. In the example of FIG. 4D, the visualindicator 108 may provide the instructions by indicating to the userthat the back portion of the hand is too close to the electronic device104. As shown, the visual indicator 108 may provide such instructions bycausing the light emitters 304 located at the right, the back-right, theback, the back-left and the left of the visual indicator 108 to emit afirst color of light, which is illustrated by the solid grey circles,but cause all of the other light emitters 304 to emit a second color oflight, which is illustrated by the solid black circles. However, inother examples, the visual indicator 108 may provide the instructions bycausing the light emitters 304 located at the right, the back-right, theback, the back-left, and the left of the visual indicator 108 to refrainfrom emitting light while causing all of the other light emitters 304 toemit light.

FIGS. 5A-5B illustrate examples of target locations for placing a handso that the electronic device 104 can capture biometric data. Forinstance, and as shown in the example of FIG. 5A, the electronic device104 includes a top surface 502 and an imaging device 504. In order forthe electronic device 104 to capture the biometric data, such as theimage data, the user places the hand (e.g., the center point of the palmof the hand) over the imaging device 504 and at the target horizontallocation. The target horizontal location may be associated with both anx-direction and a y-direction. For instance, the target horizontallocation may include the center of the imaging device 504, which isillustrated by the intersection of a first line 506 in the x-directionand a second line 508 in the y-direction.

In some instances, the electronic device 104 may allow for the hand tobe proximate to the target horizontal location when capturing thebiometric data. For instance, the electronic device 104 may allow forthe hand to be a first threshold distance 510 in front of the targethorizontal location (e.g., moving in the positive y-direction from thetarget horizontal location), a second threshold distance 512 behind thetarget horizontal location (e.g., moving in the negative y-directionfrom the target horizontal location), a third threshold distance 514 tothe left of the target horizontal location (e.g., moving in the negativex-direction from the target horizontal location), and/or a fourththreshold distance 516 to the right of the target horizontal location(e.g., moving in the positive x-direction from the target horizontallocation). In some instances, the first threshold distance 510, thesecond threshold distance 512, the third threshold distance 514, and thefourth threshold distance 516 may include the same threshold distance.In some instances, one or more of the first threshold distance 510, thesecond threshold distance 512, the third threshold distance 514, and thefourth threshold distance 516 may include a different thresholddistance. As described herein, a threshold distance may include, but isnot limited to, five millimeters, ten millimeters, twenty millimeters,and/or any other distance.

Additionally, and as shown in the example of FIG. 5B, the electronicdevice 104 may include a target vertical distance that is located adistance 518 above the imaging device 504 (e.g., in the z-direction). Insome examples, the distance 518 includes eighty-five millimeters.However, in other examples, the distance 518 may include any otherdistance. In some instances, the electronic device 104 may allow for thehand to be proximate to the target vertical distance. For instance, theelectronic device 104 may allow for the hand to be a first thresholddistance 520 above the target vertical distance and/or a secondthreshold distance 522 below the target vertical distance. In someinstances, the first threshold distance 520 is the same as the secondthreshold distance 522. In other instances, the first threshold distance520 is different than the second threshold distance 522.

As further illustrated in the example of FIG. 5B, the electronic device104 may be able to detect the hand of the user between a minimumdistance 524 above the imaging device 504 and a maximum distance 526above the imaging device 504. For instance, the distance sensor may beconfigured to detect objects, such as hands, between the minimumdistance 524 and the maximum distance 526. In some instances, theminimum distance 524 may include, but is not limited to, fivemillimeters, ten millimeters, twenty millimeters, and/or any otherdistance. Additionally, the maximum distance 526 may include, but is notlimited to, one hundred millimeters, one hundred and twenty millimeters,one hundred and fifth millimeters, and/or any other distance.

In the example of FIG. 5C, the electronic device 104 may include atarget location that includes a volumetric shape 528, such as avolumetric shape of a cone above the imaging device 504. For example,the target vertical distance may still be located the distance 518 abovethe imaging device 504 and include the first threshold distance 520 andthe second threshold distance 522. The target horizontal location maythen be located within the volumetric shape 528 and at locations thatare within the target vertical distance. In some instances, the palm ofthe hand may need to be located within the target location while inother examples, the entire hand may need to be located within the targetlocation.

In the example of FIG. 5D, the electronic device 104 may include atarget location that includes a volumetric shape 530 above the imagingdevice 504. For example, the target vertical distance may still belocated the distance 518 above the imaging deivce 504 and include thefirst threshold distance 520 and the second threshold distance 522. Thetarget horizontal location may then be located within the volumetricshape 530 and at locations that are within the target vertical distance.In some instances, the palm of the hand may need to be located withinthe target location while in other examples, the entire hand may need tobe located within the target location.

FIG. 6 illustrates an example of analyzing a hand 602 in order toidentify the center of a palm of the hand 602. For instance, theelectronic device 104 may generate image data representing an image 604depicting the hand 602. The electronic device 104 may then generatefeature data corresponding to the image data, where the feature datarepresents various attributes associated with the hand 602. The variousattributes may include at least points 606-618 located on the hand 602.For example, the electronic device 104 may identify a point 606 locatedon a first end of the wrist and a point 608 located on a second,opposite end of the wrist. The electronic device 104 may furtheridentify points 610-618 located on the bottom of the fingers of the hand602. As shown, the points 612-618 are located at intersections betweenthe fingers.

After identifying the points 606-618, the electronic device 104 maygenerate a bounding box 620 that includes all of the identified points606-618. The bounding box 620 may be associated with four additionalpoints 622-628 representing the corners of the bounding box 620. Theelectronic device 104 may then use the bounding box 620 to identify acenter point 630 of the palm of the hand 602. For example, theelectronic device 104 may determine that the center point 630 of thepalm includes the center of the bounding box 620. As such, in someexamples, the center point 630 of the palm may correspond to thehorizontal location of the hand 602.

In some instances, and as described herein, the electronic device 104may identify one or more additional attributes associated with the hand602 using the image 604. For example, since the hand 602 is oriented inthe y-direction, the electronic device 104 may determine that theorientation of the hand 602 is satisfied. The electronic device 104 mayfurther determine that the planar shape of the hand 602 is satisfiedsince the hand 602 is not in the shape of a cup, a fist, and/or the hand602 is making a gesture. Rather, the hand 602 is open such that theelectronic device 104 may analyze the image 604 to determine theattributes. Furthermore, the electronic device 104 may determine thatthe hand 602 is parallel to the imaging component of the electronicdevice 104. This may be because, based on the orientation of the hand602 with respect to the imaging component, the palm of the hand 602 ispointed towards the imaging component.

While the example of FIG. 6 describes identifying the points 606-618 andthen using the points 606-618 to determine the center point of the palm,in other examples, the electronic device 104 may identify additionaland/or alternative points on the hand 602 and then use the additionaland/or alternative points to identify the center point 630 of the palm.

FIG. 7 illustrates an example environment 700 of a materials handlingfacility 702 that includes the electronic device 104 to capturebiometric data of users. In this example, the electronic device 104generates image data depicting a palm of a user 704 and sends the imagedata to one or more backend server(s) 706 to be used to enroll the user704 for use of the user-recognition system. Generally, theuser-recognition system may include the electronic device 104 and/or theserver(s) 706.

In some instances, some or all of the user-recognition system residesremotely from the materials handling facility 702, while in otherinstances, some or all of the user-recognition system resides within orproximate to the materials handling facility 702. As FIG. 7 depicts, theuser 704 may have engaged in, or be about to engage in, a shoppingsession in the materials handling facility 702. For instance, the user704 may have selected an item 708 from an inventory location 710 (e.g.,shelf, aisle, etc.) and placed the item 708 in a tote 712 (e.g.,shopping cart). The inventory location 710 may house one or moredifferent types of items 708 and the user 704 may pick (i.e., take) oneof these items 708.

As illustrated, the materials handling facility 702 (or “facility”) mayinclude one or more sensors, such as the illustrated imaging sensor(s)714, and/or an array of other sensors located on or near the inventorylocation(s) 710. In this example, the imaging sensor(s) 714 areconfigured to capture video data within the facility 702 for use indetermining results associated with events, such as the picking of theitem 708 by the user 704. While FIG. 7 illustrates various examplesensors, the sensors in the facility 702 may comprise any other type ofsensor, such as weight sensors (e.g., load cells), microphones, and/orthe like, as described in detail below. As described in more detail withrespect to FIGS. 13 and 14, the facility 702 may be monitored and/orotherwise associated with an inventory-management system configured todetermine events in the facility 702 associated with the user 704, suchas taking items 708 that the user 704 would like to purchase. Theinventory-management system may track the items 708 selected by the user704 and maintain a virtual shopping cart which includes all of the items708 taken by the user 704. Thus, when a user 704 would like to leave thefacility 702 with the items 708 they have taken, theinventory-management system may charge a user account associated withthe user 704 for the cost of the items 708 that were taken.

As shown in FIG. 7, the user 704 may approach a checkout location 716associated with the electronic device 104. The user 704 may determinethat they would like to enroll for use of a user-recognition system inorder to checkout of the facility 702 and pay for their item(s) 708.Alternatively, or additionally, the user may interact with theelectronic device 104 upon entering the facility 702. In eitherinstance, the user 704 may determine that they would like theuser-recognition system to collect data that is usable to identify theuser 704. This data may be utilized by the user-recognition system suchthat, once enrolled, the user 704 need only scan his or her palm to beidentified by the user-recognition system in order to charge their useraccount with the purchase of their item(s) 708.

FIG. 7 illustrates an example enrollment process 718 that describes, ata high level, techniques for enrolling the user 704 for use of theuser-recognition system and for the user-recognition system updating theenrollment of the user 704 over time. The electronic device 104 maycomprise components for performing at least a portion of the techniquesof the enrollment process 718, as may the servers. Components of theserver(s) 706 are described in further detail below with reference tosubsequent figures. For example, the electronic device 104 may compriseone or more processors 720 configured to power components of theelectronic device 104 and may further include memory 722 which storescomponents that are at least partially executable by the processor(s)720, as well as other data 724. For example, the memory 722 may includea presence-detection component 726 to detect the presence of a user 704,a front-end enrollment component 728 configured to perform variousoperations for enrolling the user 704 for use of the user-recognitionsystem, and a user interface component 730 configured to controlinstructions being provided to the user 704 via the visual indicator108.

At 732, the front-end enrollment component 728 may receive a request toenroll the user 704 for use of the user-recognition system. The requestmay comprise various types of input, such as a selection made via an I/Ointerface 734 (e.g., touch screen, mouse, keyboard, speakers, etc.) forstarting an enrollment process. Additionally, the front-end enrollmentcomponent 728 may detect a speech utterance from the user 704 indicatinga request to enroll (e.g., “please enroll me,” “I would like to checkout,” etc.). Another request example may include the user 704 sliding auser ID card into an I/O interface 734, such as a credit card, driver'slicense, etc. However, any type of input may be detected as a request bythe front-end enrollment component 728.

In some examples, at 736 of the enrollment process 718, thepresence-detection component 726 may be executable by the processor(s)720 to detect a trigger indicating presence of the user 704. The triggerdetected by the presence-detection component 726 may comprise one ormore types of input. For instance, the presence-detection component 726may include logic to detect, using one or more imaging component 738(e.g., which may represent the imaging device 504) and/or one or moredistance components 740 (e.g., which may represent the distance sensors302), a palm of the user 704 over or proximate to the electronic device104. Other examples of triggers detected by the presence-detectioncomponent 726 that may indicate the presence of the user 704 may includereceiving touch input (or other input, such as a mouse click) via one ormore I/O interfaces 734 of the electronic device 104. However, any typeof input may be detected as a trigger by the presence-detectioncomponent 726 at 736. In some examples, the trigger detection at 736 maynot be performed, or may be included in or the same as receiving therequest to enroll.

After receiving the request to enroll from the user 704, the front-endenrollment component 728 may, at 742, begin generating image data 744using the one or more imaging component(s) 738 (e.g., cameras). Forinstance, the front-end enrollment component 728 may utilize the imagingcomponent(s) 738 to obtain image data 744, such as an image or picture,a sequence of consecutive images, and/or video data. The image data 744may represent the palm of the user 704 and may be used to identifycreases in the palm, veins in the palm, geometric information regardingthe palm and other parts of the hand or the user 704 and/or the like. Insome instances, while obtaining the image data 744, the user interfacecomponent 730 may cause the electronic device 104 to provideinstructions for how to place the hand of the user 704. Once thefront-end enrollment component 728 has obtained the image data 744representing the palm or other portion of the user 704, the electronicdevice 104 may send (e.g., upload, stream, etc.) the image data 744 tothe server(s) 706 over one or more networks 746 using one or morecommunication interfaces 748.

The network(s) 746 may include private networks such as an institutionalor personal intranet, public networks such as the Internet, or acombination thereof. The network(s) 746 may utilize wired technologies(e.g., wires, fiber optic cable, and so forth), wireless technologies(e.g., radio frequency, infrared, acoustic, optical, and so forth), orother connection technologies. The network(s) 746 is representative ofany type of communication network, including one or more of datanetworks or voice networks. The network(s) 746 may be implemented usingwired infrastructure (e.g., copper cable, fiber optic cable, and soforth), a wireless infrastructure (e.g., cellular, microwave, satellite,etc.), or other connection technologies.

The communication interface(s) 748 may include devices configured tocouple to personal area networks (PANs), wired and wireless local areanetworks (LANs), wired and wireless wide area networks (WANs), and soforth. For example, the communication interfaces 748 may include devicescompatible with Ethernet, Wi-Fi™, and so forth. In some examples, thecommunication interface(s) 748 may encode the image data 744 and/orother data 724 (e.g., distance data from a distance sensor) generated bythe electronic device 104 prior to sending over the network(s) 746according to the type of protocol or standard being used.

Upon receiving the image data 744, and at 750, one or more components ofthe back-end server(s) 706 may generate feature data using the imagedata 744. This feature data may be in a vector form and may representcharacteristics about the user's palm that may be used to differentiatethe palm from other user palms. It is to be appreciated that while thisenrollment process 750 describes the server(s) 706 generating thefeature data, in other instances, the electronic device 104 may beconfigured to generate the feature data and may send the feature data,in addition to or rather than the image data 744, to the servers.

At 752, one or more components of the server(s) 706 store the featuredata in an enrollment database in association with a user profile of theuser 704. That is, this palm-feature data is stored such that it may becompared to feature data generate from subsequent image data for lateridentification of the user 704 at the facility 702 or other facilitiesthat are associated with the user-recognition system.

For example, at 754, the imaging component(s) 738 receive additionalimage data 744 of the palm of the user 704, such as at a time when theuser 704 has returned to the facility 702 at a later date. After theserver(s) 706 receive the additional image data 744 from the electronicdevice 104, and at 756, the server(s) 706 may generate additionalfeature data based on the additional image data. At this point, one ormore components of the server(s) 706 may compare the additional featuredata to feature data stored in respective user profiles for the purposeof identifying the user 704 associated with the additional image data744. In this example, the user-recognition system compares theadditional feature data generated at 756 with the feature data generatedat 750 and stored in association with the user profile of the user 704and, thus, at 758, identifies the user profile. In some instances, inaddition to identifying the user profile, the user-recognition systemmay then store the additional feature data in the enrollment database inassociation with the user profile of the user 704.

FIG. 8 illustrates an example environment 800 including block diagram ofthe server(s) 706 configured to support at least a portion of thefunctionality of a user-recognition system, as well as an example flowof data within the system for enrolling the user 704 for use of theuser-recognition system.

As illustrated, the environment 800 includes a client side 802 and aserver side 804. However, this is merely illustrative, and some or allof the techniques may be performed entirely on the client side 802, orentirely on the server side 804. At “1,” a front-end enrollmentcomponent 728 may receive a request to enroll a user 704 for use of theuser-recognition system. For example, the request may comprise varioustypes of input, such as a selection made via an I/O interface 734 (e.g.,touch screen, mouse, keyboard, etc.) of a user interface elementpresented on a display for starting an enrollment process. Additionally,the front-end enrollment component 728 may detect a speech utterancefrom the user 704 indicating a request to enroll (e.g., “please enrollme,” “I would like to check out,” etc.). Another request example mayinclude the user 704 sliding a user ID card into an I/O interface 734,such as a credit card, driver's license, etc. However, any type of inputmay be detected as a request by the front-end enrollment component 728.

Upon receiving the request to enroll, the front-end enrollment component728 may activate or otherwise utilize the imaging component(s) 738 togenerate image data 744 representing a palm of the user 704. At “2,” theelectronic device 104 then captures image data 744 and, at “3”, sendsthe image data 744 to the server(s) 706. For instance, the electronicdevice 104 may encode and send the image data 744 over the network(s)746 to the server(s) 706. Further, in some instances, some of the imagesmay be removed if there are not in focus, do not have a threshold levelof discriminability of the characteristics of the palm of the user, orthe like. This removal may occur on the client side 802 and/or theserver side 804.

At “4,” the server(s) 706 receive the image data and, at “5”, apalm-feature generation component 806 of a palm-identification component808 may extract palm-feature data from the image data 744. In someexamples, prior to extracting the palm-feature data, the palm-featuregeneration component 806 may perform various operations for processingthe image data 744 prior to extracting the palm-feature data. Forinstance, the palm-feature generation component 806 may initiallyperform user detection to determine that the image data 744 represents apalm of a user 704. For instance, the palm-feature generation component806 may utilize an Integrated Sensor Processor (ISP) that performshardware-based user detection techniques. In some examples, varioussoftware techniques may additionally, or alternatively be performed. Ineither instance, a bounding box may be output around the detected handof the user 704 for an image depicting at least a portion of the user704 and represented by the image data 744. Further, the palm-featuregeneration component 806 may perform hand-pose estimation in order toalign the palm of the user 704 with a common coordinate system. Afteraligning the image of the hand into a common coordinate section, theportion of the image data corresponding to the palm may be identifiedand cropped. This remaining portion of the image data may thereafter beused to extract features therefrom by, for example, running a neuralnetwork on the cropped section of the image data. In some examples,hand-pose estimation may improve the extraction of features representingthe palm of the user 704. Once the hand of the user 704 has beenaligned, the palm-feature generation component 806 may extract features(e.g., palm-feature data) from the image data 744. In some examples, thetrained model(s) may utilize a triples loss function which convertsimage data 744 into a feature embedding in a metric space (e.g.,palm-feature data), which may allow for comparisons with subsequentfeature vectors using, for example, squared distance calculation.

At “6,” the palm-feature aggregation component 810 may aggregate featuredata (e.g., palm-feature data) from various image data 744. Forinstance, the image data 744 may represent the hand of the user 704 atdifferent angles, under different lighting conditions, or otherdiffering characteristics. The palm-feature aggregation component 810may aggregate the palm-feature data together, such as by averaging outfeature vectors.

At “7,” the quality-check component 812 may perform a quality check onthe palm-feature data. For example, the quality-check component 812 mayutilize trained model(s) to determine an overall metric of the qualityof the extracted palm-feature data. If the overall metric is poor, orbelow a threshold quality level, the user-recognition system may requestto acquire additional image data 744. In addition, or in thealternative, the quality-check component 812 may perform a de-dupingprocess to ensure that the user associated with the palm-feature datahasn't already enrolled in the system. If the overall quality metric isgood or acceptable, and if the de-duping process does not reveal thatthe user has previously enrolled in the system, a backend enrollmentcomponent 814 may aggregate the data at “8.”

For example, at “8” the backend enrollment component 814 may aggregatethe palm-feature data and enroll the user at “9” in an enrollmentdatabase 816. The backend enrollment component 814 may storeassociations (e.g., mappings) between the palm-feature data with a userprofile of the user 704 requesting to be enrolled for use of theuser-recognition system.

FIG. 9 illustrates an example environment 900 including a block diagramof the server(s) 706 configured to support at least a portion of thefunctionality of a user-recognition system, as well as an example flowof data within the system for identifying a user 704 of theuser-recognition system and, potentially, updating the enrollment of theuser. As illustrated, the environment 900 includes a client side 902 anda server side 904. However, this is merely illustrative, and some or allof the techniques may be performed entirely on the client side 902, orentirely on the server side 904.

At “1,” a user requests to sign in with the user-recognition system. Forexample, the presence-detection component 726 may be executable by theprocessor(s) 720 to detect a trigger indicating presence of the user704. The trigger detected by the presence-detection component 726 maycomprise one or more types of input. For instance, thepresence-detection component 726 may include logic to detect, using oneor more imaging components 738, a portion of a user 704 (e.g., a handover the imaging component(s) 738 of the electronic device 104). Otherexamples of triggers detected by the presence-detection component 726that may indicate the presence of the user 704 may include receivingtouch input (or other input, such as a mouse click) via one or more I/Ointerfaces 734 of the electronic device 104. However, any type of inputmay be detected as a trigger by the presence-detection component 726.

Upon identifying the request to sign in from the user, at “2” one ormore imaging components 738 may generate image data 744 representing apalm of the user 704 and/or another portion of the user. At “3,” theelectronic device 104 may send the image data 744 to the server(s) 706.For instance, the electronic device 104 may encode and send the imagedata 744 over the network(s) 746 to the server(s) 706. Again, some ofthe image data 744 may be discarded based on the image data being out offocus, having a discriminability that is less than the threshold, and/orthe like.

At “4,” the servers may receive the image data 744 and, at “5”, thepalm-feature generation component 806 may extract palm-feature data fromthe image data 744. In some examples, prior to extracting thepalm-feature data, the palm-feature generation component 806 may performvarious operations for processing the image data 744 prior to extractingthe palm-feature data. For instance, the palm-feature generationcomponent 806 may initially perform palm detection to determine that theimage data 744 represents a hand of a user 704. For instance, thepalm-feature generation component 806 may utilize an Integrated SensorProcessor (ISP) that performs hardware-based user detection techniques.In some examples, various software techniques may additionally, oralternatively be performed. In either instance, a bounding box may beoutput around the detected hand of the user 704 for an image depictingthe user 704 and represented by the image data 744. Further, thepalm-feature generation component 806 may perform hand pose estimationto align the face of the user 704 with a common coordinate system. Insome examples, hand pose estimation may improve the extraction offeatures representing the hand of the user 704. Once the hand of theuser 704 has been aligned, the palm-feature generation component 806 mayextract features (e.g., palm-feature data) from the image data 744. Insome examples, the trained model(s) may utilize a triples loss functionwhich converts the image data 744 into a feature embedding in a metricspace (e.g., palm-feature data), which may allow for comparisons withsubsequent feature vectors using, for example, squared distancecalculation.

At “6,” the palm-feature aggregation component 810 may aggregate featuredata (e.g., palm-feature data) from various image data 744. Forinstance, the image data 744 may represent the hand of the user 704 atdifferent angles, under different lighting conditions, or otherdiffering characteristics. The palm-feature aggregation component 810may aggregate the palm-feature data together, such as by averaging outfeature vectors.

At “7,” a palm-feature correspondence component 906 may generate one ormore scores indicating a similarity between the aggregated featuresassociated with the image data 744 and respective feature data stored inassociation with respective user profiles. In some examples, thesecorrespondence scores may be determined, at least in part, on“distances” between the feature vector associated with the image dataand respective feature vectors of the respective palm-feature datastored in association with user profiles in the enrollment database 816.

At “8,” an identity-determination component 908 may determine theidentity of the user based on the correspondence scores. For example,the identity-determination component 908 may identity the user profileassociated with the feature vector having the closest distance to thefeature vector associated with the image data 744 and may deem theassociated user the user associated with the image data 744.

At “9”, in some instances the enrollment-update component 910 may usethe recently received palm-feature data associated with the image datato update the enrollment of the identified user. For example, theenrollment-update component 910 may detect occurrence of a predefinedevent that results in the updating of the enrollment data. This mayinclude a predefined amount of time having elapsed since the most-recentor least-recent feature data being associated with the profile, based ona characteristic of the transaction occurring at the facility inassociation with the image data 744 (e.g., a cost or number of items),based on a threshold amount of change between the current feature dataand previous feature data associated with the user profile, based on anexplicit request from the user associated with the user profiled, and/orthe like. In some instances, the predefined event may comprise an auditcomponent determining that the received palm-feature data corresponds tothe identified user with a confidence level that is greater than thepreviously discussed high threshold confidence level. That is, while therecognition process described with reference to steps “7”-“8” may beperformed with reference to enrollment data, the audit component maydetermine a confidence level using both the enrollment data and imageand/or feature data associate with previous recognition attempts. If theaudit component thereafter computes a confidence level that is greaterthan the relatively high confidence level, then the enrollment-updatecomponent 910 may determine to update the enrollment data of theidentified user.

At “10”, the enrollment-update component 910 updates the enrollment dataassociated with the corresponding user profile in the enrollmentdatabase 816. As described above, this may include storing the featuredata and/or image data alongside existing feature data and/or image dataassociated with the profile, averaging the existing feature data withthe new feature data, and/or the like.

FIG. 10 illustrates example components of the electronic device 104configured to support at least a portion of the functionality of auser-recognition system. In some examples, the user-recognition systemdescribed herein may be supported entirely, or at least partially, bythe electronic device 104 in conjunction with the server(s) 706. Theelectronic device 104 may include one or more hardware processors 720(processors) configured to execute one or more stored instructions. Theprocessor(s) 720 may comprise one or more cores. The electronic device104 may include one or more input/output (I/O) interface(s) 734 to allowthe processor 720 or other portions of the electronic device 104 tocommunicate with other devices. The I/O interface(s) 734 may compriseInter-Integrated Circuit (I2C), Serial Peripheral Interface bus (SPI),Universal Serial Bus (USB) as promulgated by the USB Implementers Forum,RS-232, and so forth.

The electronic device 104 may also include one or more communicationinterfaces 748. The communication interface(s) 748 are configured toprovide communications between the electronic device 104 and otherdevices, such as the server(s) 706, the interface devices, routers, andso forth. The communication interface(s) 748 may include devicesconfigured to couple to personal area networks (PANs), wired andwireless local area networks (LANs), wired and wireless wide areanetworks (WANs), and so forth. For example, the communication interfaces308 may include devices compatible with Ethernet, Wi-Fi™, and so forth.

The electronic device 104 may further include one or more distancecomponents 740. The distance component(s) 740 may include, but are notlimited to, IR sensor(s), LIDAR sensor(s), and/or any other type ofsensor that may detect a distance of an object.

The electronic device 104 may also include one or more busses or otherinternal communications hardware or software that allow for the transferof data between the various modules and components of the electronicdevice 104.

As shown in FIG. 10, the electronic device 104 includes one or morememories 722. The memory 722 comprises one or more computer-readablestorage media (CRSM). The CRSM may be any one or more of an electronicstorage medium, a magnetic storage medium, an optical storage medium, aquantum storage medium, a mechanical computer storage medium, and soforth. The memory 722 provides storage of computer-readableinstructions, data structures, program modules, and other data for theoperation of the electronic device 104. A few example functional modulesare shown stored in the memory 722, although the same functionality mayalternatively be implemented in hardware, firmware, or as a system on achip (SOC).

The memory 722 may include at least one operating system (OS) 1004. TheOS 1004 is configured to manage hardware resource devices such as theI/O interface(s) 734, the imaging sensor(s) 714, the visual indicator108, and the distance component(s) 740, and provide various services toapplications or modules executing on the processor(s) 720. The OS 1004may implement a variant of the FreeBSD™ operating system as promulgatedby the FreeBSD Project; other UNIX™ or UNIX-like variants; a variationof the Linux™ operating system as promulgated by Linus Torvalds; theWindows® Server operating system from Microsoft Corporation of Redmond,Wash., USA; and so forth.

One or more of the following components may also be stored in the memory722. These modules may be executed as foreground applications,background tasks, daemons, and so forth.

A communication component 1006 may be configured to establishcommunications with the server(s) 706 and/or or other devices. Thecommunications may be authenticated, encrypted, and so forth.

An enrollment component 1008 may be configured to perform variousoperations for enrolling a user for use of the user-recognition system(e.g., similar to the backend enrollment component 814). For instance,the enrollment component 1008 may perform various operations, and/orcause other components to perform various operations, to enroll users inthe user-recognition system. In some instance, the enrollment component1008 may at least partly control a palm-identification component 1010that performs operations for analyzing image data 744 depicting a palmor other portion of the user. In some examples, the enrollment component1008 may cause the palm-identification component 1010 to analyze theimage data 744 and extract features which represent a palm of the user,such as palm-feature data 1012.

After obtaining, determining, and/or generating the palm-feature data1012, the enrollment component 1008 may enroll the user in an enrollmentdatabase 1014 which indicates that the user is enrolled for use of theuser-recognition system. In some examples, the enrollment component 1008may associate, or map, the various data to a user profile/account 1016that is associated with the user. For example, the enrollment component1008 may map, for each enrolled user, respective palm-feature data 1012to corresponding user profiles 1016 in the enrollment database 1014.Thus, the enrollment database 1014 may store indications of userprofiles 1016, as well as the data for users associated with each of theuser profiles 1016. When a user is enrolled for use of theuser-recognition system, the enrollment component 1008 may map, or storean association, between the user's palm-feature data 1012 with the userprofile 1016 for that user.

Further, the enrollment component 1008 may cause a training component1018 to train one or more trained models 1020. The training component1018 may utilize the palm-feature data 1012 to train the trainedmodel(s) 1020 to perform various operations for extracting and/orgenerating, from the image data 744, the palm-feature data 1012. Thetrained model(s) 1020 may comprise any type of model, such asmachine-learning models, including but not limited to artificial neuralnetworks, classifiers, decision trees, support vector machines, Bayesiannetworks, and so forth.

As a specific example, the trained model(s) 1020 may include or compriseone or more convolution neural networks (CNNs), recursive neuralnetworks, and/or any other artificial networks, that are trained toanalyze image data 744 received as input, and extract, determine,identify, generate, etc., palm-feature data 1012 representing a palm ofthe user. As a specific example, the palm-feature data 1012 may comprisea 128-dimension feature vector representing the palm of the user. Inexamples where the trained model(s) 1020 include one or more CNNs,various functions may be utilized to transform the image data 744 into ametric space, such as a triplet loss function. Thus, the trainingcomponent 1018 may train the CNNs of the trained model(s) 1020 usingvarious functions, such as a triplet loss function, to extract,identity, or otherwise determine palm-feature data 1012 from input imagedata 744. Once in the metric space, extracted feature data may becompared, or matched, by computing a distance between the extractedfeature data and feature data stored in the enrollment database 1014.For instance, when feature data is extracted from the image data 744into palm-feature data 1012 by the trained model(s) 1020, the extractedpalm-feature data 1012 may then be compared to stored data in theenrollment database 1014 to identify a user profile for the userrepresented in the input image data 744. For instance, the extractedpalm-feature data 1012 may comprise a vector that is compared withstored vectors in the enrollment database 1014 to identify which storedvectors have the smallest “distance” between the extracted feature data.The smaller the distance, the closer the strength of correspondencebetween the extracted feature data and the stored feature datarepresenting users that are enrolled for use of the user-recognitionsystem. In some examples, other calculations may be performed, such asfinding a cosine of an angle between two vectors, depending on thenetwork utilized by the trained model(s) 1020. However, any type ofmodels may be utilized for the trained model(s) 1020.

The palm-identification component 1010 may include varioussub-components for performing various operations. For instance, thepalm-identification component 1010 may include a palm-feature generationcomponent 1022 to extract or otherwise generate feature data from theimage data 744 (e.g., similar to the palm-feature generation component806). The palm-feature generation component 1010 may utilize the trainedmodel(s) 1020, and/or include algorithms, to perform any type of featureextraction method, or embedding, to analyze the image data 744 andextract the palm-feature data 1012. For instance, the palm-featuregeneration component 1022 may utilize state-of-the-art models, such asclustering, artificial neural networks, scale-invariant featuretransform, edge detection, or any other type of extraction or embeddingtechnology, to extract palm-feature data 1012 from the image data 744.

The palm-identification component 1010 may further include apalm-feature aggregation component 1024 configured to aggregate featuredata for a user (e.g., similar to the palm-feature aggregation component810). For instance, the palm-feature aggregation component 1024 maycombine palm-feature data 1012 that has been extracted from a group ofimages depicting the user, such as by averaging the features in thepalm-feature data 1012.

Once a user is enrolled for use of the user-recognition system, anidentity-determination component 1026 may be utilized to determineand/or verify an identity of a user that interacted with the electronicdevice 104. For example, the electronic device 104 may use the imagedata 744 and the identity-determination component 1026 (which may besimilar to the identity-determination component 908) to determine anidentity of the user, where the enrollment database 1014 indicates theidentity of the user by, for example, indicating the user profile 1016that is associated with that user's identity.

The identity-determination component 1026 may cause a palm-featurecorrespondence component 1028 to perform various operations fordetermining or identifying a user whose palm is depicted in the receivedimage data 744. For example, the palm-feature correspondence component1028 may compare the palm-feature data 1012 for the received image data744 with palm-feature data 1012 stored in the enrollment database 1014for different user profiles 1016 of users enrolled in theuser-recognition system in order to determine user profiles 1016 for oneor more users whose respective palm-feature data 1012 correspond to theextracted palm-feature data 1012. In some instances, the scorecalculated by the palm-feature correspondence component 1028 may becompared to a threshold and, if the score is greater than the threshold,may result in identification of the user. If multiple user profiles areassociated with scores that are greater than the threshold, then theuser profile associated with the highest may be deemed to be associatedwith the image data 744 and/or further analysis may be performed toidentify the appropriate user. Further, in some instances, theuser-recognition system may employ set-reduction techniques to identify,based on an initial comparison, a top “N” group of user profiles 1016 ofusers whose respective palm-feature data 1012 most strongly correspondto the extracted palm-feature data 1012. In some examples, a single userprofile 1016 may be determined as corresponding to the inputpalm-feature data 1012. However, in some examples, a group of top “N”candidates may be identified by the trained model(s) 1020 ascorresponding with a threshold amount of strength (e.g., 50%correspondence, 105% correspondence, etc.) to the extracted palm-featuredata 1012. A second level of deeper analysis may then be performed toidentify a single user from the “N” candidates.

Further, the memory 722 may store an enrollment-update component 1030configured to update the palm-feature data 1012 stored in associationwith user profiles to allow for removal of stale feature data and use ofmore recent feature data (e.g., similar to the enrollment-updatecomponent 910). As introduced above, as a user provides image data ofthe user's palm over time, the enrollment-update component 1030 may usefeature data from this new image data to generate and store additionalfeature data associated with the user. Further, the enrollment-updatecomponent 1030 may remove or lessen a weight associated with olderfeature data.

In addition, the memory 722 may store an audit component 1032 configuredto perform one or more auditing processes in response to occurrence ofone or more predefined events. For example, the audit component 1032 mayperform a nightly auditing processes comprising rich comparison ofpalm-feature data associated with respective user profiles to oneanother to identify any errors previously made by the system. Afteridentifying an error, the system may correct the error and may also thisinformation to further train the trained model(s) 1020 utilizingtechniques similar to those performed by the enrollment component 1008.

Additionally, the memory 722 may store a quality-check component 1034which determines an overall metric of the quality of the extractedpalm-feature data 1012. For instance, the quality-check component 1034may determine that additional image data 744 needs to be obtained for auser for various reasons.

The memory 722 may also store a location detection component 1036configured to determine the location of the hand with respect to theelectronic device 104 (and/or the imaging component of the electronicdevice 104). For instance, and as described herein, the locationdetection component 1036 may determine one or more points located on thehand. The location detection component 1036 may then use the one or morepoints to identify the center of the palm of the hand with respect tothe electronic device 104. In some instances, the location detectioncomponent 1036 determines the location of the hand at given timeintervals. For instance, the location detection component 1036 maydetermine the location of the user's hand every millisecond, second,and/or the like. In some examples, the location detection component 1036determines the location of the user's hand using each frame representedby the image data 744, every other frame represented by the image data744, every fifth frame represented by the image data 744, and/or thelike.

The memory 722 may also store the user interface component 730configured to generate and/or update the user interfaces describedherein. For instance, once the hand is detected, the user interfacecomponent 730 may cause the visual indicator 108 to output instructionsfor placing the hand. The user interface component 730 may then use thelocations determined by the location detection component 1036 to presentand/or update the visual indicator 108 indicating the current locationof the hand. Once the location detection component 1036 determines thelocation of the hand is proximate to the target location, the userinterface component 730 may cause the visual indicator 108 to indicatethat the electronic device 104 has captured the biometric data.

FIGS. 11A-12 illustrate various processes for providing instructionsassociated with inputting biometric data. The processes described hereinare illustrated as collections of blocks in logical flow diagrams, whichrepresent a sequence of operations, some or all of which may beimplemented in hardware, software or a combination thereof. In thecontext of software, the blocks may represent computer-executableinstructions stored on one or more computer-readable media that, whenexecuted by one or more processors, program the processors to performthe recited operations. Generally, computer-executable instructionsinclude routines, programs, objects, components, data structures and thelike that perform particular functions or implement particular datatypes. The order in which the blocks are described should not beconstrued as a limitation, unless specifically noted. Any number of thedescribed blocks may be combined in any order and/or in parallel toimplement the process, or alternative processes, and not all of theblocks need be executed.

FIGS. 11A-11B illustrate a flow diagram of an example process 1100 forproviding instructions associated with placing a hand at a targetlocation relative to the electronic device 104. At 1102, the process1100 may include generating first sensor data using a first distancesensor and at 1104, the process 1100 may include analyzing the firstsensor data to determine that the first distance sensor detected a handover a first portion of an electronic device. For instance, theelectronic device 104 may generate the first sensor data using the firstdistance sensor. The first distance sensor may be associated with thefirst portion of the electronic device. The electronic device 104 maythen analyze the first sensor data to determine that the first distancesensor detected the hand. As such, the electronic device 104 maydetermine that the hand is located over the first portion of theelectronic device.

At 1106, the process 1100 may include generating second sensor datausing a second distance sensor and at 1108, the process 1100 may includeanalyzing the second sensor data to determine that the second distancesensor did not detect the hand over a second portion of the electronicdevice. For instance, the electronic device 104 may generate the secondsensor data using the second distance sensor. The second distance sensormay be associated with the second portion of the electronic device. Theelectronic device 104 may then analyze the second sensor data todetermine that the second distance sensor did not the hand. As such, theelectronic device 104 may determine that the hand is not located overthe second portion of the electronic device.

At 1110, the process 1100 may include causing a first portion of avisual indicator to indicate that the hand was detected over the firstportion of the electronic device. For instance, based on the firstdistance sensor detecting the hand, the electronic device 104 may cause,at a first time, the first portion of the visual indicator to output afirst indication that the hand was detected over the first portion ofthe electronic device 104. The first portion of the visual indicator maybe associated with the first distance sensor such that the first portionof the visual indicator provides indications when hands are detected bythe first distance sensor. In some instances, such as when the visualindicator includes light emitters (e.g., a light ring), the firstindication includes emitting light using one or more of the lightemitters located at the first portion of the visual indicator. In someinstances, such as when the visual indicator includes a display, thefirst visual indication includes causing the first portion of thedisplay to present the first indication.

At 1112, the process 1100 may include causing a second portion of thevisual indicator to indicate that the hand was not detected over thesecond portion of the electronic device. For instance, based on thesecond distance sensor not detecting the hand, the electronic device 104may cause, at the first time, the second portion of the visual indicatorto indicate that the hand was not detected over the second portion ofthe electronic device 104. The second portion of the visual indicatormay be associated with the second distance sensor such that the secondportion of the visual indicator provides indications when hands aredetected by the second distance sensor. In some instances, such as whenthe visual indicator includes the light emitters, one or more of thelight emitters associated with the second portion of the visualindicator may refrain from emitting light. In some instances, such aswhen the visual indicator includes the display, the second portion ofthe display may refrain from presenting content.

At 1114, the process 1100 may include generating third sensor data usingthe first distance sensor and at 1116, the process 1100 may includeanalyzing the third sensor data to determine that the first distancesensor detected the hand over the first portion of the electronicdevice. For instance, the electronic device 104 may generate the thirdsensor data using the first distance sensor. The electronic device 104may then analyze the third sensor data to determine that the firstdistance sensor detected the hand. As such, the electronic device 104may determine that the hand is still located over the first portion ofthe electronic device.

At 1118, the process 1100 may include generating fourth sensor datausing the second distance sensor and at 1120, the process 1100 mayinclude analyzing the fourth sensor data to determine that the seconddistance sensor detected the hand over the second portion of theelectronic device. For instance, the electronic device 104 may generatethe fourth sensor data using the second distance sensor. The electronicdevice 104 may then analyze the fourth sensor data to determine that thesecond distance sensor detected the hand. As such, the electronic device104 may determine that the hand is located over the second portion ofthe electronic device.

At 1122, the process 1100 may include causing the first portion of thevisual indicator to indicate that the hand was detected over the firstportion of the electronic device. For instance, based on the firstdistance sensor again detecting the hand, the electronic device 104 maycause, at a second time, the first portion of the visual indicator tooutput a second indication that the hand was detected over the firstportion of the electronic device 104. In some instances, such as whenthe visual indicator includes the light emitters, the second indicationincludes emitting light using one or more of the light emitters locatedat the first portion of the visual indicator. In some instances, such aswhen the visual indicator includes the display, the second visualindication includes causing the first portion of the display to presentsecond indication.

At 1124, the process 1100 may include causing the second portion of thevisual indicator to indicate that the hand was detected over the secondportion of the electronic device. For instance, based on the seconddistance sensor detecting the hand, the electronic device 104 may cause,at the second time, the second portion of the visual indicator to outputa third indication that the hand was detected over the second portion ofthe electronic device 104. In some instances, such as when the visualindicator includes the light emitters, the third indication includesemitting light using one or more of the light emitters located at thesecond portion of the visual indicator. In some instances, such as whenthe visual indicator includes the display, the third visual indicationincludes causing the second portion of the display to present thirdindication.

At 1126, the process 1100 may include generating image data using animaging device and at 1128, the process 1100 may include identifying anaccount based at least in part on the image data. For instance, once thehand is at the target location relative to the electronic device 104(e.g., the first distance sensor and the second distance sensor detectthe hand), the electronic device 104 may generate the image data. Theelectronic device 104 may then analyze the image data to identify theaccount. For example, the electronic device 104 may analyze feature datacorresponding to the image data with reference to feature data stored inassociation with the user profile. Based on the analysis, the electronicdevice 104 may identify a match between the feature data correspondingto the image data and the feature data associated with the user profile.The electronic device 104 may use the match to identify the userprofile.

FIG. 12 illustrates a flow diagram of an example process 1200 forproviding instructions associated with placing a portion of a user at atarget location relative to the electronic device 104. At 1202, theprocess 1200 may include generating sensor data using one or moresensors and at 1204, the process 1200 may include determining, based atleast in part on the sensor data, a location and an angle of a portionof a user. For instance, the electronic device 104 may generate thesensor data using one or more distance sensors and/or one or moreimaging devices. The electronic device 104 may then analyze the sensordata to determine that the portion of the user is located at thelocation relative to the electronic device 104. In some instances, suchas when the sensor data is generated using the one or more distancesensors, the electronic device 104 may determine the location based onwhich distance sensor(s) detected the portion of the user. In someinstances, such as when the sensor data is generated using the one ormore imaging devices, the electronic device 104 may determine thelocation based on analyzing features represented by the sensor data.

The electronic device 104 may also analyze the sensor data to determinethe angle associated with the portion of the user. In some instances,such as when the sensor data is generated by the one or more distancesensors, the electronic device 104 may determine the angle based ondetected distances from the distance sensors to the portion of the user.In some instances, such as when the sensor data is generated by the oneor more imaging devices, the electronic device 104 may determine theangle based on analyzing features represented by the sensor data,

At 1206, the process 1200 may include determining if the locationsatisfies a target vertical distance. For instance, the electronicdevice 104 may determine if the location of the portion of the usersatisfies the target vertical distance. In some instances, theelectronic device 104 may determine that the location satisfies thetarget vertical distance when the location is within a range associatedwith the target vertical distance and determine that the location doesnot satisfy the target vertical distance when the location is outside of(e.g., greater than or less than) the range associated with the targetvertical distance.

If, at 1206, it is determined that the location does not satisfy thetarget vertical distance, then at 1208, the process 1200 may includecausing a visual indicator to provide an instruction associated withadjusting the portion of the user. For instance, if the electronicdevice 104 determines that the location does not satisfy the targetvertical distance, then the electronic device 104 may provide theinstruction that the portion of the user is either too low or too high.In some instances, such as when the visual indicator includes aplurality of light emitters (e.g., a light ring), the visual indicatormay provide the instruction by emitting a color of light, emitting alight pattern, and/or emitting a brightness of light. In some instances,such as when the visual indicator includes a display, the visualindicator may provide the instruction by displaying content on thedisplay.

However, if, at 1206, it is determined that the location satisfies thetarget vertical distance, then at 1210, the process 1200 may includedetermining if the location satisfies a target horizontal location. Forinstance, the electronic device 104 may determine if the location of theportion of the user satisfies the target horizontal location. In someinstances, the electronic device 104 may determine that the locationsatisfies the target horizontal location when the location is within afirst range associated with the x-direction and a second rangeassociated with the y-direction. Additionally, the electronic device 104may determine that the location does not satisfy the target horizontallocation when the location is outside of the first range associated withthe x-direction or the second range associated with the y-direction.

If, at 1210, it is determined that the location does not satisfy thetarget horizontal location, then at 1208, the process 1200 may againinclude causing the visual indicator to provide an instructionassociated with adjusting the portion of the user. For instance, if theelectronic device 104 determines that the location does not satisfy thetarget horizontal location, then the electronic device 104 may providethe instruction that the portion of the user is either too far left, toofar forward, too far right, and/or too far backward. In some instances,such as when the visual indicator includes the plurality of lightemitters, the visual indicator may provide the instruction by emittinglight using a portion of the light emitters that is associated with thelocation of the portion of the user. In some instances, such as when thevisual indicator includes the display, the visual indicator may providethe instruction by displaying content using a portion of the displaythat is associated with the location of the portion of the user.

However, if, at 1210, it is determined that the location satisfies thetarget horizontal location, then at 1212, the process 1200 may includedetermining if the angle satisfies a target angle. For instance, theelectronic device 104 may determine if the angle of the portion of theuser satisfies the target angle. In some instances, the electronicdevice 104 may determine that the angle satisfies the target angle whenthe angle is within a range associated with the target angle.Additionally, the electronic device 104 may determine that the angledoes not satisfy the target angle when the angle is outside of thetarget angle.

If, at 1212, it is determined that the angle does not satisfy the targetangle, then at 1208, the process 1200 may again include causing thevisual indicator to provide an instruction associated with adjusting theportion of the user. For instance, if the electronic device 104determines that the angle does not satisfy the target angle, then theelectronic device 104 may provide the instruction that the portion ofthe user is too far angled. In some instances, such as when the visualindicator includes the plurality of light emitters, the visual indicatormay provide the instruction by emitting a first color of light, a firstlight pattern, and/or a first brightness of light using a first portionof the light emitters and emitting a second color of light, a secondlight pattern, and/or a second brightness of light using a secondportion of the light emitters. In some instances, such as when thevisual indicator includes the display, the visual indicator may providethe instruction by displaying first content using a first portion of thedisplay and second content using a second portion of the display.

However, if, at 1212, it is determined that the angle satisfies thetarget angle, then at 1214, the process may include causing the visualindicator to indicate that the portion of the user is at the targetlocation. For instance, if the electronic device 104 determines that theangle satisfies the target angle, then the electronic device 104 mayindicate that the location of the portion of the user is at the targetlocation. In some instances, such as when the visual indicator includesthe plurality of light emitters, the visual indicator may provide theindication by emitting a color of light, a light pattern, and/or abrightness of light using the light emitters. In some instances, such aswhen the visual indicator includes the display, the visual indicator mayprovide the indication by displaying content.

It should be noted that, as illustrated in FIG. 12, the process mayrepeat back at 1202 after providing the instruction at 1208. It shouldalso be noted that, in some instances, the order to 1206, 1210, and/or1212 may be switched and/or the process 1200 may not include one or moreof 1206, 1210, or 1212.

FIGS. 13 and 14 represent an illustrative materials handlingenvironment, such as the materials handling facility 602, in which thetechniques described herein may be applied to cameras monitoring theenvironments as described below. However, the following description ismerely one illustrative example of an industry and environment in whichthe techniques described herein may be utilized.

An implementation of a materials handling facility 1302 (e.g., facility1302) configured to store and manage inventory items is illustrated inFIG. 13. A materials handling facility 1302 comprises one or morephysical structures or areas within which one or more items 1304(1),1304(2), . . . , 1304(Q) (generally denoted as 1304) may be held. Asused in this disclosure, letters in parenthesis such as “(Q)” indicatean integer result. The items 1304 comprise physical goods, such asbooks, pharmaceuticals, repair parts, electronic gear, groceries, and soforth.

The facility 1302 may include one or more areas designated for differentfunctions with regard to inventory handling. In this illustration, thefacility 1302 includes a receiving area 1306, a storage area 1308, and atransition area 1310. The receiving area 1306 may be configured toaccept items 1304, such as from suppliers, for intake into the facility1302. For example, the receiving area 1306 may include a loading dock atwhich trucks or other freight conveyances unload the items 1304.

The storage area 1308 is configured to store the items 1304. The storagearea 1308 may be arranged in various physical configurations. In oneimplementation, the storage area 1308 may include one or more aisles1312. The aisle 1312 may be configured with, or defined by, inventorylocations 1314 on one or both sides of the aisle 1312. The inventorylocations 1314 may include one or more of shelves, racks, cases,cabinets, bins, floor locations, or other suitable storage mechanismsfor holding or storing the items 1304. The inventory locations 1314 maybe affixed to the floor or another portion of the facility's structure,or may be movable such that the arrangements of aisles 1312 may bereconfigurable. In some implementations, the inventory locations 1314may be configured to move independently of an outside operator. Forexample, the inventory locations 1314 may comprise a rack with a powersource and a motor, operable by a computing device to allow the rack tomove from one location within the facility 1302 to another.

One or more users 1316(1), 1316(2), . . . , 1316(U) (generally denotedas 1316), totes 1318(1), 1318(2), . . . , 1318(T) (generally denoted as1318) or other material handling apparatus may move within the facility1302. For example, the users 1316 may move about within the facility1302 to pick or place the items 1304 in various inventory locations1314, placing them on the totes 1318 for ease of transport. Anindividual tote 1318 is configured to carry or otherwise transport oneor more items 1304. For example, a tote 1318 may include a basket, acart, a bag, and so forth. In other implementations, other agencies suchas robots, forklifts, cranes, aerial drones, and so forth, may moveabout the facility 1302 picking, placing, or otherwise moving the items1304.

One or more sensors 1320 may be configured to acquire information in thefacility 1302. The sensors 1320 in the facility 1302 may include sensorsfixed in the environment (e.g., ceiling-mounted cameras) or otherwise,such as sensors in the possession of users (e.g., mobile phones,tablets, etc.). The sensors 1320 may include, but are not limited to,cameras 1320(1), weight sensors, radio frequency (RF) receivers,temperature sensors, humidity sensors, vibration sensors, and so forth.The sensors 1320 may be stationary or mobile, relative to the facility1302. For example, the inventory locations 1314 may contain cameras1320(1) configured to acquire images of pick or placement of items 1304on shelves, of the users 1316(1) and 1316(2) in the facility 1302, andso forth. In another example, the floor of the facility 1302 may includeweight sensors configured to determine a weight of the users 1316 orother object thereupon.

During operation of the facility 1302, the sensors 1320 may beconfigured to provide information suitable for identifying new locationsof objects or other occurrences within the facility 1302. For example, aseries of images acquired by a camera 1320(1) may indicate removal of anitem 1304 from a particular inventory location 1314 by one of the users1316 and placement of the item 1304 on or at least partially within oneof the totes 1318.

While the storage area 1308 is depicted as having one or more aisles1312, inventory locations 1314 storing the items 1304, sensors 1320, andso forth, it is understood that the receiving area 1306, the transitionarea 1310, or other areas of the facility 1302 may be similarlyequipped. Furthermore, the arrangement of the various areas within thefacility 1302 is depicted functionally rather than schematically. Forexample, multiple different receiving areas 1306, storage areas 1308,and transition areas 1310 may be interspersed rather than segregated inthe facility 1302.

The facility 1302 may include, or be coupled to, an inventory managementsystem 1322. The inventory management system 1322 is configured toidentify interactions with and between users 1316, devices such assensors 1320, robots, material handling equipment, computing devices,and so forth, in one or more of the receiving area 1306, the storagearea 1308, or the transition area 1310. These interactions may includeone or more events 1324. For example, events 1324 may include the entryof the user 1316 to the facility 1302, stocking of items 1304 at aninventory location 1314, picking of an item 1304 from an inventorylocation 1314, returning of an item 1304 to an inventory location 1314,placement of an item 1304 within a tote 1318, movement of users 1316relative to one another, gestures by the users 1316, and so forth. Otherevents 1324 involving users 1316 may include the user 1316 providingauthentication information in the facility 1302, using a computingdevice at the facility 1302 to authenticate identity to the inventorymanagement system 1322, and so forth. Some events 1324 may involve oneor more other objects within the facility 1302. For example, the event1324 may comprise movement within the facility 1302 of an inventorylocation 1314, such as a counter mounted on wheels. Events 1324 mayinvolve one or more of the sensors 1320. For example, a change inoperation of a sensor 1320, such as a sensor failure, change inalignment, and so forth, may be designated as an event 1324. Continuingthe example, movement of a camera 1320(1) resulting in a change in theorientation of the field of view 1328 (such as resulting from someone orsomething bumping the camera 1320(1)) (e.g. camera) may be designated asan event 1324.

By determining the occurrence of one or more of the events 1324, theinventory management system 1322 may generate output data 1326. Theoutput data 1326 comprises information about the event 1324. Forexample, where the event 1324 comprises an item 1304 being removed froman inventory location 1314, the output data 1326 may comprise an itemidentifier indicative of the particular item 1304 that was removed fromthe inventory location 1314 and a user identifier of a user that removedthe item.

The inventory management system 1322 may use one or more automatedsystems to generate the output data 1326. For example, an artificialneural network, one or more classifiers, or other automated machinelearning techniques may be used to process the sensor data from the oneor more sensors 1320 to generate output data 1326. The automated systemsmay operate using probabilistic or non-probabilistic techniques. Forexample, the automated systems may use a Bayesian network. In anotherexample, the automated systems may use support vector machines togenerate the output data 1326 or the tentative results. The automatedsystems may generate confidence level data that provides informationindicative of the accuracy or confidence that the output data 1326 orthe tentative data corresponds to the physical world.

The confidence level data may be generated using a variety oftechniques, based at least in part on the type of automated system inuse. For example, a probabilistic system using a Bayesian network mayuse a probability assigned to the output as the confidence level.Continuing the example, the Bayesian network may indicate that theprobability that the item depicted in the image data corresponds to anitem previously stored in memory is 135%. This probability may be usedas the confidence level for that item as depicted in the image data.

In another example, output from non-probabilistic techniques such assupport vector machines may have confidence levels based on a distancein a mathematical space within which the image data of the item and theimages of previously stored items have been classified. The greater thedistance in this space from a reference point such as the previouslystored image to the image data acquired during the occurrence, the lowerthe confidence level.

In yet another example, the image data of an object such as an item1304, user 1316, and so forth, may be compared with a set of previouslystored images. Differences between the image data and the previouslystored images may be assessed. For example, differences in shape, color,relative proportions between features in the images, and so forth. Thedifferences may be expressed in terms of distance with a mathematicalspace. For example, the color of the object as depicted in the imagedata and the color of the object as depicted in the previously storedimages may be represented as coordinates within a color space.

The confidence level may be determined based at least in part on thesedifferences. For example, the user 1316 may pick an item 1304(1) such asa perfume bottle that is generally cubical in shape from the inventorylocation 1314. Other items 1304 at nearby inventory locations 1314 maybe predominately spherical. Based on the difference in shape (cube vs.sphere) from the adjacent items, and the correspondence in shape withthe previously stored image of the perfume bottle item 1304(1) (cubicaland cubical), the confidence level that the user 606 has picked up theperfume bottle item 1304(1) is high.

In some situations, the automated techniques may be unable to generateoutput data 1326 with a confidence level above a threshold result. Forexample, the automated techniques may be unable to distinguish whichuser 1316 in a crowd of users 1316 has picked up the item 1304 from theinventory location 1314. In other situations, it may be desirable toprovide human confirmation of the event 1324 or of the accuracy of theoutput data 1326. For example, some items 1304 may be deemed agerestricted such that they are to be handled only by users 1316 above aminimum age threshold.

In instances where human confirmation is desired, sensor data associatedwith an event 1324 may be processed to generate inquiry data. Theinquiry data may include a subset of the sensor data associated with theevent 1324. The inquiry data may also include one or more of one or moretentative results as determined by the automated techniques, orsupplemental data. The subset of the sensor data may be determined usinginformation about the one or more sensors 1320. For example, camera datasuch as the location of the camera 1320(1) within the facility 1302, theorientation of the camera 1320(1), and a field of view 1328 of thecamera 1320(1) may be used to determine if a particular location withinthe facility 1302 is within the field of view 1328. The subset of thesensor data may include images that may show the inventory location 1314or that the item 1304 was stowed. The subset of the sensor data may alsoomit images from other cameras 1320(1) that did not have that inventorylocation 1314 in the field of view 1328. The field of view 1328 maycomprise a portion of the scene in the facility 1302 that the sensor1320 is able to generate sensor data about.

Continuing the example, the subset of the sensor data may comprise avideo clip acquired by one or more cameras 1320(1) having a field ofview 1328 that includes the item 1304. The tentative results maycomprise the “best guess” as to which items 1304 may have been involvedin the event 1324. For example, the tentative results may compriseresults determined by the automated system that have a confidence levelabove a minimum threshold.

The facility 1302 may be configured to receive different kinds of items1304 from various suppliers and to store them until a customer orders orretrieves one or more of the items 1304. A general flow of items 1304through the facility 1302 is indicated by the arrows of FIG. 13.Specifically, as illustrated in this example, items 1304 may be receivedfrom one or more suppliers, such as manufacturers, distributors,wholesalers, and so forth, at the receiving area 1306. In variousimplementations, the items 1304 may include merchandise, commodities,perishables, or any suitable type of item 1304, depending on the natureof the enterprise that operates the facility 1302. The receiving of theitems 1304 may comprise one or more events 1324 for which the inventorymanagement system 1322 may generate output data 1326.

Upon being received from a supplier at receiving area 1306, the items1304 may be prepared for storage. For example, items 1304 may beunpacked or otherwise rearranged. The inventory management system 1322may include one or more software applications executing on a computersystem to provide inventory management functions based on the events1324 associated with the unpacking or rearrangement. These inventorymanagement functions may include maintaining information indicative ofthe type, quantity, condition, cost, location, weight, or any othersuitable parameters with respect to the items 1304. The items 1304 maybe stocked, managed, or dispensed in terms of countable, individualunits or multiples, such as packages, cartons, crates, pallets, or othersuitable aggregations. Alternatively, some items 1304, such as bulkproducts, commodities, and so forth, may be stored in continuous orarbitrarily divisible amounts that may not be inherently organized intocountable units. Such items 1304 may be managed in terms of measurablequantity such as units of length, area, volume, weight, time, duration,or other dimensional properties characterized by units of measurement.Generally speaking, a quantity of an item 1304 may refer to either acountable number of individual or aggregate units of an item 1304 or ameasurable amount of an item 1304, as appropriate.

After arriving through the receiving area 1306, items 1304 may be storedwithin the storage area 1308. In some implementations, like items 1304may be stored or displayed together in the inventory locations 1314 suchas in bins, on shelves, hanging from pegboards, and so forth. In thisimplementation, all items 1304 of a given kind are stored in oneinventory location 1314. In other implementations, like items 1304 maybe stored in different inventory locations 1314. For example, tooptimize retrieval of certain items 1304 having frequent turnover withina large physical facility 1302, those items 1304 may be stored inseveral different inventory locations 1314 to reduce congestion thatmight occur at a single inventory location 1314. Storage of the items1304 and their respective inventory locations 1314 may comprise one ormore events 1324.

When a customer order specifying one or more items 1304 is received, oras a user 1316 progresses through the facility 1302, the correspondingitems 1304 may be selected or “picked” from the inventory locations 1314containing those items 1304. In various implementations, item pickingmay range from manual to completely automated picking. For example, inone implementation, a user 1316 may have a list of items 1304 theydesire and may progress through the facility 1302 picking items 1304from inventory locations 1314 within the storage area 1308, and placingthose items 1304 into a tote 1318. In other implementations, employeesof the facility 1302 may pick items 1304 using written or electronicpick lists derived from customer orders. These picked items 1304 may beplaced into the tote 1318 as the employee progresses through thefacility 1302. Picking may comprise one or more events 1324, such as theuser 1316 in moving to the inventory location 1314, retrieval of theitem 1304 from the inventory location 1314, and so forth.

After items 1304 have been picked, they may be processed at a transitionarea 1310. The transition area 1310 may be any designated area withinthe facility 1302 where items 1304 are transitioned from one location toanother or from one entity to another. For example, the transition area1310 may be a packing station within the facility 1302. When the item1304 arrives at the transition area 1310, the items 1304 may betransitioned from the storage area 1308 to the packing station. Thetransitioning may comprise one or more events 1324. Information aboutthe transition may be maintained by the inventory management system 1322using the output data 1326 associated with those events 1324.

In another example, if the items 1304 are departing the facility 1302 alist of the items 1304 may be obtained and used by the inventorymanagement system 1322 to transition responsibility for, or custody of,the items 1304 from the facility 1302 to another entity. For example, acarrier may accept the items 1304 for transport with that carrieraccepting responsibility for the items 1304 indicated in the list. Inanother example, a customer may purchase or rent the items 1304 andremove the items 1304 from the facility 1302. The purchase or rental maycomprise one or more events 1324.

The inventory management system 1322 may access or generate sensor dataabout the facility 1302 and the contents therein including the items1304, the users 1316, the totes 1318, and so forth. The sensor data maybe acquired by one or more of the sensors 1320, data provided by othersystems, and so forth. For example, the sensors 1320 may include cameras1320(1) configured to acquire image data of scenes in the facility 1302.The image data may comprise still images, video, or a combinationthereof. The image data may be processed by the inventory managementsystem 1322 to determine a location of the user 1316, the tote 1318, theidentity of the user 1316, and so forth. As used herein, the identity ofthe user may represent a unique identifier of the user (e.g., name,number associated with user, username, etc.), an identifier thatdistinguishes the user amongst other users being identified with theenvironment, or the like.

The inventory management system 1322, or systems coupled thereto, may beconfigured to identify a profile associated with the user 1316, as wellas to determine other candidate users. In one implementation, thisdetermination may comprise comparing sensor data with previously storedidentity data. Identifying the profile associated with the user 1316 maybe identified before, during, or after entry to the facility 1302.Identifying of the profile associated with the user 1316 may comprisecomparing sensor data associated with the user 1316 in the facility 1302to previously stored user data.

In some instances, the inventory management system group users withinthe facility into respective sessions. That is, the inventory managementsystem 1322 may utilize the sensor data to determine groups of usersthat are effectively “together” (e.g., shopping together). In someinstances, a particular session may include multiple users that enteredthe facility 1302 together and, potentially, that navigate the facilitytogether. For example, when a family of two adults and two childrenenter the facility together, the inventory management system mayassociate each user with a particular session. Locating sessions inaddition to individual users may help in determining the outcome ofindividual events, given that users within a session may not onlyindividually pick or return or otherwise interact with items, but mayalso pass the items back and forth amongst each other. For instance, achild in the above example may pick the box of cereal before handing thebox to her mother, who may place it in her tote 1318. Noting the childand the mother as belonging to the same session may increase the chancesof successfully adding the box of cereal to the virtual shopping cart ofthe mother.

By determining the occurrence of one or more events 1324 and the outputdata 1326 associated therewith, the inventory management system 1322 isable to provide one or more services to the users 1316 of the facility1302. By utilizing one or more human associates to process inquiry dataand generate response data that may then be used to produce output data1326, overall accuracy of the system may be enhanced. The enhancedaccuracy may improve the user experience of the one or more users 1316of the facility 1302. In some examples, the output data 1326 may betransmitted over a network 1330 to one or more server(s) 706.

FIG. 14 illustrates a block diagram of the one or more server(s) 706.The server(s) 706 may be physically present at the facility 1402, may beaccessible by the network 1430, or a combination of both. The server(s)706 do not require end-user knowledge of the physical location andconfiguration of the system that delivers the services. Commonexpressions associated with the server(s) 706 may include “on-demandcomputing,” “software as a service (SaaS),” “cloud services,” “datacenters,” and so forth. Services provided by the server(s) 706 may bedistributed across one or more physical or virtual devices.

The server(s) 706 may include one or more hardware processors 1402(processors) configured to execute one or more stored instructions. Theprocessors 1402 may comprise one or more cores. The server(s) 706 mayinclude one or more input/output (I/O) interface(s) 1404 to allow theprocessor 1402 or other portions of the server(s) 706 to communicatewith other devices. The I/O interfaces 1404 may compriseInter-Integrated Circuit (I2C), Serial Peripheral Interface bus (SPI),Universal Serial Bus (USB) as promulgated by the USB Implementers Forum,and so forth.

The server(s) 706 may also include one or more communication interfaces1406. The communication interfaces 1406 are configured to providecommunications between the server(s) 706 and other devices, such as thesensors 1420, the interface devices, routers, and so forth. Thecommunication interfaces 1406 may include devices configured to coupleto personal area networks (PANs), wired and wireless local area networks(LANs), wired and wireless wide area networks (WANs), and so forth. Forexample, the communication interfaces 1406 may include devicescompatible with Ethernet, Wi-Fi™, and so forth. The server(s) 706 mayalso include one or more busses or other internal communicationshardware or software that allow for the transfer of data between thevarious modules and components of the server(s) 706.

The server(s) 706 may also include a power supply 1440. The power supply1440 is configured to provide electrical power suitable for operatingthe components in the server(s) 706.

As shown in FIG. 14, the server(s) 706 includes one or more memories1410. The memory 1410 comprises one or more computer-readable storagemedia (CRSM). The CRSM may be any one or more of an electronic storagemedium, a magnetic storage medium, an optical storage medium, a quantumstorage medium, a mechanical computer storage medium, and so forth. Thememory 1410 provides storage of computer-readable instructions, datastructures, program modules, and other data for the operation of theserver(s) 706. A few example functional modules are shown stored in thememory 1410, although the same functionality may alternatively beimplemented in hardware, firmware, or as a system on a chip (SOC).

The memory 1410 may include at least one operating system (OS) component1412. The OS component 1412 is configured to manage hardware resourcedevices such as the I/O interface(s) 1404, the communicationinterface(s) 1408, and provide various services to applications orcomponents executing on the processor(s) 1402. The OS component 1412 mayimplement a variant of the FreeBSD™ operating system as promulgated bythe FreeBSD Project; other UNIX™ or UNIX-like variants; a variation ofthe Linux™ operating system as promulgated by Linus Torvalds; theWindows® Server operating system from Microsoft Corporation of Redmond,Wash., USA; and so forth.

One or more of the following components may also be stored in the memory1410. These components may be executed as foreground applications,background tasks, daemons, and so forth. A communication component 1414may be configured to establish communications with one or more of thesensors 1320, one or more electronic devices 104, one or more of thedevices used by associates, other server(s) 706, or other devices. Thecommunications may be authenticated, encrypted, and so forth.

The memory 1410 may store an inventory management system 1416. Theinventory management system 1416 is configured to provide the inventoryfunctions as described herein with regard to the inventory managementsystem 1322. For example, the inventory management system 1416 maydetermine movement of items 1304 in the facility 1202, generate userinterface data, and so forth.

The inventory management system 1416 may access information stored inone or more data stores 1418 in the memory 1410. The data store 1418 mayuse a flat file, database, linked list, tree, executable code, script,or other data structure to store the information. In someimplementations, the data store 1418 or a portion of the data store 1418may be distributed across one or more other devices including otherserver(s) 706, network attached storage devices, and so forth.

The data store 1418 may include physical layout data 1420. The physicallayout data 1420 provides a mapping of physical locations within thephysical layout of devices and objects such as the sensors 1320,inventory locations 1314, and so forth. The physical layout data 1420may indicate the coordinates within the facility 1302 of an inventorylocation 1314, sensors 1320 within view of that inventory location 1314,and so forth. For example, the physical layout data 1420 may includecamera data comprising one or more of a location within the facility1302 of a camera 1320(1), orientation of the camera 1320(1), theoperational status, and so forth. Continuing example, the physicallayout data 1420 may indicate the coordinates of the camera 1320(1), panand tilt information indicative of a direction that the field of view1328 is oriented along, whether the camera 1320(1) is operating ormalfunctioning, and so forth.

In some implementations, the inventory management system 1416 may accessthe physical layout data 1420 to determine if a location associated withthe event 1324 is within the field of view 1328 of one or more sensors1320. Continuing the example above, given the location within thefacility 1302 of the event 1324 and the camera data, the inventorymanagement system 1416 may determine the cameras 1320(1) that may havegenerated images of the event 1324.

The item data 1422 comprises information associated with the items 1304.The information may include information indicative of one or moreinventory locations 1314 at which one or more of the items 1304 arestored. The item data 1422 may also include order data, SKU or otherproduct identifier, price, quantity on hand, weight, expiration date,images of the item 1304, detail description information, ratings,ranking, and so forth. The inventory management system 1416 may storeinformation associated with inventory management functions in the itemdata 1422.

The data store 1418 may also include sensor data 1424. The sensor data1424 comprises information acquired from, or based on, the one or moresensors 1320. For example, the sensor data 1424 may comprise 3Dinformation about an object in the facility 1302. As described above,the sensors 1320 may include a camera 1320(1), which is configured toacquire one or more images. These images may be stored as the image data1426. The image data 1426 may comprise information descriptive of aplurality of picture elements or pixels. Non-image data 1428 maycomprise information from other sensors 1320, such as input from themicrophones 1320, weight sensors 1320, and so forth.

User data 1430 may also be stored in the data store 1418. The user data1430 may include identity data, information indicative of a profile,purchase history, location data, images of the user 1316, demographicdata, and so forth. Individual users 1316 or groups of users 1316 mayselectively provide user data 1430 for use by the inventory managementsystem 1322. The individual users 1316 or groups of users 1316 may alsoauthorize collection of the user data 1430 during use of the facility1302 or access to user data 1430 obtained from other systems. Forexample, the user 1316 may opt-in to collection of the user data 1430 toreceive enhanced services while using the facility 1302.

In some implementations, the user data 1430 may include informationdesignating a user 1316 for special handling. For example, the user data1430 may indicate that a particular user 1316 has been associated withan increased number of errors with respect to output data 1326. Theinventory management system 1416 may be configured to use thisinformation to apply additional scrutiny to the events 1324 associatedwith this user 1316. For example, events 1324 that include an item 1304having a cost or result above the threshold amount may be provided tothe associates for processing regardless of the determined level ofconfidence in the output data 1326 as generated by the automated system.

The inventory management system 1416 may include one or more of alocating component 1432, identification component 1434, eventdetermination component 1436, and inquiry component 1438.

The locating component 1432 functions to locate items or users withinthe environment of the facility to allow the inventory management system1416 to assign certain events to the correct users. That is, thelocating component 1432 may assign unique identifiers to users as theyenter the facility and, with the users' consent, may locating theposition of the users throughout the facility 1302 over the time theyremain in the facility 1302. The locating component 1432 may performthis locating using sensor data 1424, such as the image data 1426. Forexample, the locating component 1432 may receive the image data 1426 andmay use techniques to identify profiles associated with users from theimages. After identifying a particular profile associated with a userwithin the facility, the locating component 1432 may then locating theuser within the images as the user moves throughout the facility 1302.Further, should the locating component 1432 temporarily “lose” aparticular user, the locating component 1432 may again attempt toidentify the profiles associated with the users within the facilitybased on techniques.

Therefore, upon receiving the indication of the time and location of theevent in question, the locating component 1432 may query the data store1418 to determine which one or more users were at or within a thresholddistance of the location of the event at the particular time of theevent. Further, the locating component 1432 may assign differentconfidence levels to different users, with the confidence levelsindicating how likely it is that each corresponding user is the userthat is in fact associated with the event of interest.

The locating component 1432 may access the sensor data 1424 in order todetermine this location data of the user and/or items. The location dataprovides information indicative of a location of an object, such as theitem 1304, the user 1316, the tote 1318, and so forth. The location maybe absolute with respect to the facility 1302 or relative to anotherobject or point of reference. Absolute terms may comprise a latitude,longitude, and altitude with respect to a geodetic reference point.Relative terms may include a location of 25.4 meters (m) along an x-axisand 75.2 m along a y-axis as designated by a floor plan of the facility1302, 5.2 m from an inventory location 1314 along a heading of 169°, andso forth. For example, the location data may indicate that the user1316(1) is 25.2 m along the aisle 1312(1) and standing in front of theinventory location 1314. In comparison, a relative location may indicatethat the user 1316(1) is 32 cm from the tote 1318 at a heading of 73°with respect to the tote 1318. The location data may include orientationinformation, such as which direction the user 1316 is facing. Theorientation may be determined by the relative direction the user's 1316body is facing. In some implementations, the orientation may be relativeto the interface device. Continuing the example, the location data mayindicate that the user 1316(1) is oriented with a heading of 0°, orlooking north. In another example, the location data may indicate thatthe user 1316 is facing towards the interface device.

The identification component 1434 is configured to identify an object.In one implementation, the identification component 1434 may beconfigured to identify an item 1304. In another implementation, theidentification component 1434 may be configured to identify a profileassociated with the user 1316. For example, the identification component1434 may use techniques to process the image data 1426 and identify theprofile associated with the user 1316 depicted in the images bycomparing the characteristics in the image data 1426 with previouslystored results. The identification component 1434 may also access datafrom other sensors 1320, such as from an RFID reader 1320, an RFreceiver 1320, fingerprint sensors, and so forth.

The event determination component 1436 is configured to process thesensor data 1424 and generate output data 1326. The event determinationcomponent 1436 may access information stored in the data store 1418including, but not limited to, event description data 1442, confidencelevels 1444, or threshold values 1446.

The event description data 1442 comprises information indicative of oneor more events 1324. For example, the event description data 1442 maycomprise predefined profiles that designate movement of an item 1304from an inventory location 1314 with the event 1324 of “pick”. The eventdescription data 1442 may be manually generated or automaticallygenerated. The event description data 1442 may include data indicativeof triggers associated with events occurring in the facility 1302. Anevent may be determined as occurring upon detection of the trigger. Forexample, sensor data 1424 such as a change in weight from a weightsensor 1320(6) at an inventory location 1314 may trigger detection of anevent of an item 1304 being added or removed from the inventory location1314. In another example, the trigger may comprise an image of the user1316 reaching a hand toward the inventory location 1314. In yet anotherexample, the trigger may comprise two or more users 1316 approaching towithin a threshold distance of one another.

The event determination component 1436 may process the sensor data 1424using one or more techniques including, but not limited to, artificialneural networks, classifiers, decision trees, support vector machines,Bayesian networks, and so forth. For example, the event determinationcomponent 1436 may use a decision tree to determine occurrence of the“pick” event 1324 based on sensor data 1424. The event determinationcomponent 1436 may further use the sensor data 1424 to determine one ormore tentative results 1448. The one or more tentative results 1448comprise data associated with the event 1324. For example, where theevent 1324 comprises a disambiguation of users 1316, the tentativeresults 1448 may comprise a list of possible user identities. In anotherexample, where the event 1324 comprises a disambiguation between items,the tentative results 1448 may comprise a list of possible itemidentifiers. In some implementations, the tentative result 1448 mayindicate the possible action. For example, the action may comprise theuser 1316 picking, placing, moving an item 1304, damaging an item 1304,providing gestural input, and so forth.

In some implementations, the tentative results 1448 may be generated byother components. For example, the tentative results 1448 such as one ormore possible identities or locations of the user 1316 involved in theevent 1324 may be generated by the locating component 1432. In anotherexample, the tentative results 1448 such as possible items 1304 that mayhave been involved in the event 1324 may be generated by theidentification component 1434.

The event determination component 1436 may be configured to provide aconfidence level 1444 associated with the determination of the tentativeresults 1448. The confidence level 1444 provides indicia as to theexpected level of accuracy of the tentative result 1448. For example, alow confidence level 1444 may indicate that the tentative result 1448has a low probability of corresponding to the actual circumstances ofthe event 1324. In comparison, a high confidence level 1444 may indicatethat the tentative result 1448 has a high probability of correspondingto the actual circumstances of the event 1324.

In some implementations, the tentative results 1448 having confidencelevels 1444 that exceed the threshold result 1446 may be deemed to besufficiently accurate and thus may be used as the output data 1326. Forexample, the event determination component 1436 may provide tentativeresults 1448 indicative of the three possible items 1304(1), 1304(2),and 1304(3) corresponding to the “pick” event 1324. The confidencelevels 1444 associated with the possible items 1304(1), 1304(2), and1304(3) may be 25%, 70%, 142%, respectively. Continuing the example, thethreshold result may be set such that confidence level 1444 of 140% aredeemed to be sufficiently accurate. As a result, the event determinationcomponent 1436 may designate the “pick” event 1324 as involving item1304(3).

The inquiry component 1438 may be configured to use at least a portionof the sensor data 1424 associated with the event 1324 to generateinquiry data 1450. In some implementations, the inquiry data 1450 mayinclude one or more of the tentative results 1448 or supplemental data1452. The inquiry component 1438 may be configured to provide inquirydata 1450 to one or more devices associated with one or more humanassociates.

An associate user interface is presented on the respective devices ofassociates. The associate may generate response data 1454 by selecting aparticular tentative result 1448, entering new information, indicatingthat they are unable to answer the inquiry, and so forth.

The supplemental data 1452 comprises information associated with theevent 1224 or that may be useful in interpreting the sensor data 1424.For example, the supplemental data 1452 may comprise previously storedimages of the items 1304. In another example, the supplemental data 1452may comprise one or more graphical overlays. For example, the graphicaloverlays may comprise graphical user interface elements such as overlaysdepicting indicia of an object of interest. These indicia may comprisehighlights, bounding boxes, arrows, and so forth, that have beensuperimposed or placed atop the image data 1426 during presentation toan associate.

The inquiry component 1438 processes the response data 1454 provided bythe one or more associates. The processing may include calculating oneor more statistical results associated with the response data 1454. Forexample, statistical results may include a count of the number of timesassociates selected a particular tentative result 1448, determination ofa percentage of the associates that selected a particular tentativeresult 1448, and so forth.

The inquiry component 1438 is configured to generate the output data1326 based at least in part on the response data 1454. For example,given that a majority of the associates returned response data 1454indicating that the item 1304 associated with the “pick” event 1324 isitem 1304(5), the output data 1326 may indicate that the item 1304(5)was picked.

The inquiry component 1438 may be configured to selectively distributeinquiries to particular associates. For example, some associates may bebetter suited to answering particular types of inquiries. Performancedata, such as statistical data about the performance of the associates,may be determined by the inquiry component 1438 from the response data1454 provided by the associates. For example, information indicative ofa percentage of different inquiries in which the particular associateselected response data 1454 that disagreed with the majority ofassociates may be maintained. In some implementations, test or practiceinquiry data 1450 having a previously known correct answer may beprovided to the associate for training or quality assurance purposes.The determination of the set of associates to use may be based at leastin part on the performance data.

By using the inquiry component 1438, the event determination component1436 may be able to provide high reliability output data 1326 thataccurately represents the event 1324. The output data 1326 generated bythe inquiry component 1438 from the response data 1454 may also be usedto further train the automated systems used by the inventory managementsystem 1416. For example, the sensor data 1424 and the output data 1326,based on response data 1454, may be provided to one or more of thecomponents of the inventory management system 1416 for training inprocess improvement. Continuing the example, this information may beprovided to an artificial neural network, Bayesian network, and soforth, to further train these systems such that the confidence level1444 and the tentative results 1448 produced in the future for the sameor similar input is improved.

In some instances, the server(s) 706 may further include one or more ofthe components illustrated in FIG. 10 with respect to the electronicdevice 104. In such instances, the server(s) 706 may perform one or moreof the processes described herein with respect to the electronic device104. Additionally, the server(s) 706 may send, to the electronic device104, data (e.g., other data 724) associated with the performedprocesses. For instance, the data may indicate the locations of theportions of users when the users are using the electronic device 104.

While the foregoing invention is described with respect to the specificexamples, it is to be understood that the scope of the invention is notlimited to these specific examples. Since other modifications andchanges varied to fit particular operating requirements and environmentswill be apparent to those skilled in the art, the invention is notconsidered limited to the example chosen for purposes of disclosure, andcovers all changes and modifications which do not constitute departuresfrom the true spirit and scope of this invention.

Although the application describes embodiments having specificstructural features and/or methodological acts, it is to be understoodthat the claims are not necessarily limited to the specific features oracts described. Rather, the specific features and acts are merelyillustrative some embodiments that fall within the scope of the claimsof the application.

What is claimed is:
 1. An electronic device comprising: distance sensors; an imaging device; light emitters; one or more processors; and one or more computer-readable media storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: generating first sensor data using a first distance sensor of the distance sensors; analyzing the first sensor data to determine that the first distance sensor detected the hand over a first portion of the electronic device; generating second sensor data using a second distance sensor of the distance sensors; analyzing the second sensor data to determine that the second distance sensor did not detect the hand over a second portion of the electronic device; based at least in part on the first distance sensor detecting the hand over the first portion of the electronic device, causing, at a first time, a first portion of the light emitters to output first light indicating that the hand is located over the first portion of the electronic device; based at least in part on the second distance sensor not detecting the hand over the second portion of the electronic device, causing, at the first time, a second portion of the light emitters to refrain from outputting second light indicating that the hand is located over the second portion of the electronic device; generating third sensor data using the first distance sensor; analyzing the third sensor data to determine that the first distance sensor again detected the hand over the first portion of the electronic device; generating fourth sensor data using the second sensor; analyzing the fourth sensor data to determine that the second distance sensor detected the hand over the second portion of the electronic device; based at least in part on the first distance sensor again detecting the hand over the first portion of the electronic device and the second distance sensor detecting the hand over the second portion of the electronic device, causing, at a second time, the light emitters to output third light indicating that the hand is located at a target location over the electronic device; generating, using the imaging device, image data representing the hand; analyzing first feature data corresponding to the image data with reference to second feature data associated with a user profile; and determining that the image data corresponds to the user profile.
 2. The electronic device as recited in claim 1, the operations further comprising: generating fifth sensor data using the first distance sensor; analyzing the fifth sensor data to determine that the first distance sensor detected a first portion of the hand located within a target vertical distance to the electronic device; generating sixth sensor data using the second distance sensor; analyzing the sixth sensor data to determine that the second distance sensor detected a second portion of the hand located outside of the target vertical distance to the electronic device; based at least in part on the first distance sensor detecting the first portion of the hand located within the target vertical distance, causing, at a third time, the first portion of the light emitters to output fourth light indicating that the first portion of the hand is located within the target vertical distance; and based at least in part on the second distance sensor detecting the second portion of the hand located outside of the target vertical distance, causing, at the third time, the second portion of the light emitters to output fifth light indicating that the second portion of the hand is located outside of the target vertical distance.
 3. The electronic device as recited in claim 1, the operations further comprising: generating fifth sensor data using one or more of the distance sensors; analyzing the fifth sensor data to determine that the hand is located outside of a target vertical distance to the electronic device; based at least in part on the hand being located outside the target vertical distance, causing, at a third time, the light emitters to output fourth light indicating that the hand is located outside of the target vertical distance; generating sixth sensor data using the one or more of the distance sensors; analyzing the sixth sensor data to determine that the hand is located within the target vertical distance to the electronic device; and based at least in part on the hand being located within the target vertical distance, causing, at a fourth time, the light emitters to output fifth light indicating that the hand is located within of the target vertical distance.
 4. An electronic device comprising: one or more sensors; a visual indicator; one or more processors; and one or more computer-readable media storing instructions that, when executed by the one or more processors, cause the electronic device to perform operations comprising: generating first sensor data using the one or more sensors; determining, based at least in part on the first sensor data, that a portion of a user is located at a first location relative to the electronic device; identifying a first portion of a visual indicator that is associated with the first location; causing, at a first time, the first portion of the visual indicator to output a first indication that indicates that the portion of the user is located at the first location; generating second sensor data using the one or more sensors; determining, based at least in part on the second sensor data, that the portion of the user is located at a target location relative to the electronic device; causing, at a second time, the first portion of the visual indicator to output a second indication that indicates that the portion of the user is located at the target location; and causing, at the second time, a second portion of the visual indicator to output a third indication that indicates that the portion of the user is located at the target location.
 5. The electronic device as recited in claim 4, wherein: generating the first sensor data comprises: generating a first portion of the first sensor data using a first sensor of the one or more sensors, the first sensor being associated with the first location relative to the electronic device; and generating a second portion of the first sensor data using a second sensor of the one or more sensors, the second sensor being associated with a second location relative to the electronic device; and determining that the portion of the user is located at the first location relative to the electronic device comprises: determining, based at least in part on the first portion of the first sensor data, that the first sensor detected the portion of the user; and determining, based at least in part on the second portion of the first sensor data, that the second sensor did not detect the portion of the user.
 6. The electronic device as recited in claim 4, wherein: generating the second sensor data comprises: generating a first portion of the second sensor data using a first sensor of the one or more sensors, the first sensor being associated with the first location relative to the electronic device; and generating a second portion of the second sensor data using a second sensor of the one or more sensors, the second sensor being associated with a second location relative to the electronic device; and determining that the portion of the user is located at the target location relative to the electronic device comprises: determining, based at least in part on the first portion of the second sensor data, that the first sensor detected the portion of the user; and determining, based at least in part on the second portion of the second sensor data, that the second sensor detected the portion of the user.
 7. The electronic device as recited in claim 4, the operations further comprising: determining, based at least in part on the first sensor data, that the portion of the user is located outside of a second location relative to the electronic device; and causing, at the first time, the second portion of the visual indicator to indicate that the portion of the user is located outside of the second location.
 8. The electronic device as recited in claim 7, wherein: causing the first portion of the visual indicator to output the first indication that indicates that the portion of the user is located at the first location comprises causing, at the first time, the first portion of the visual indicator to output first light; and causing the second portion of the visual indicator to indicate that the portion of the user is located outside of the second location comprises causing, at the first time, the second portion of the visual indicator to refrain from outputting second light.
 9. The electronic device as recited in claim 4, the operations further comprising: generating third sensor data using the one or more sensors; determining, based at least in part on the third sensor data, that an angle associated with the portion of the user is outside of a target angle; and causing, at a third time, the visual indicator to output a fourth indication that indicates that the angle associated with the portion of the user is outside of the target angle.
 10. The electronic device as recited in claim 9, wherein causing the visual indicator to output the fourth indication that indicates that the angle associated with the portion of the user is outside of the target angle comprises: causing, at the third time, a third portion of the visual indicator to output a first light color; and causing, at the third time, a fourth portion of the visual indicator to output a second light color that is different than the first light color.
 11. The electronic device as recited in claim 4, the operations further comprising: generating third sensor data using the one or more sensors; determining, based at least in part on the third sensor data, that the portion of the user is located outside of a target vertical distance to the electronic device; and causing, at a third time, the visual indicator to output a fourth indication that indicates that the portion of the user is located outside of the target vertical distance.
 12. The electronic device as recited in claim 11, the operations further comprising: generating fourth sensor data using the one or more sensors; determining, based at least in part on the fourth sensor data, that the portion of the user is located within the target vertical distance to the electronic device; and causing, at a fourth time that is later than the third time, the visual indicator to output a fifth indication that indicates that the portion of the user is located within the target vertical distance.
 13. The electronic device as recited in claim 4, wherein: the visual indicator comprises a light ring with a plurality of light emitters; and causing the first portion of the visual indicator to output the first indication that indicates that the portion of the user is located at the first location comprises: causing a first portion of the light emitters to emit first light, the first portion of the light emitters being associated with the first location; and causing a second portion of the light emitters to refrain from emitting second light, the second portion of the light emitters being associated with a second location relative to the electronic device.
 14. The electronic device as recited in claim 4, further comprising at least one speaker, and wherein the operations further comprise, before generating the second sensor data, outputting, using the at least one speaker, sound associated with instructions for placing the portion of the user at the target location.
 15. The electronic device as recited in claim 4, the operations further comprising: generating image data using the one or more sensors; analyzing first feature data corresponding to the image data with reference to second feature data associated with a user profile; and determining that the image data corresponds to the user profile.
 16. A method comprising: generating first sensor data using an electronic device; determining, based at least in part on the first sensor data, that a portion of a user is located at a first location relative to the electronic device; identifying a first portion of a visual indicator that is associated with the first location; causing, at a first time, the first portion of the visual indicator to output a first indication; generating second sensor data using the one or more sensors; determining, based at least in part on the second sensor data, that the portion of the user is located at a second location relative to the electronic device; identifying the first portion of the visual indicator that is associated with the second location; causing, at a second time, the first portion of the visual indicator to output a second indication; identifying a second portion of the visual indicator that is associated with the second location; and causing, at the second time, the second portion of the visual indicator to output a third indication.
 17. The method as recited in claim 16, wherein: generating the first sensor data comprises: generating a first portion of the first sensor data using a first sensor of the electronic device, the first sensor being associated with the first location relative to the electronic device; and generating a second portion of the first sensor data using a second sensor of the electronic device, the second sensor being associated with a third location relative to the electronic device; and determining that the portion of the user is located at the first location relative to the electronic device comprises: determining, based at least in part on the first portion of the first sensor data, that the first sensor detected the portion of the user; and determining, based at least in part on the second portion of the first sensor data, that the second sensor did not detect the portion of the user.
 18. The method as recited in claim 16, wherein: generating the second sensor data comprises: generating a first portion of the second sensor data using a first sensor of the electronic device, the first sensor being associated with the first location relative to the electronic device; and generating a second portion of the second sensor data using a second sensor of the electronic device, the second sensor being associated with a third location relative to the electronic device; and determining that the portion of the user is located at the second location relative to the electronic device comprises: determining, based at least in part on the first portion of the second sensor data, that the first sensor detected the portion of the user; and determining, based at least in part on the second portion of the second sensor data, that the second sensor also detected the portion of the user.
 19. The method as recited in claim 16, further comprising: determining, based at least in part on the first sensor data, that the portion of the user is located outside of a third location relative to the electronic device; and causing, at the first time, the second portion of the visual indicator to indicate that the portion of the user is located outside of the second location.
 20. The method as recited in claim 16, further comprising: generating third sensor data using the electronic device; determining, based at least in part on the third sensor data, that an angle associated with the portion of the user is outside of a target angle; and causing, at a third time, the visual indicator to output a fourth indication that indicates that the angle associated with the portion of the user is outside of the target angle. 